Vol 15 no 2 february 2016 by ijlter.org

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International Journal of Learning, Teaching And Educational Research

Vol.15 No.2

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International Journal of Learning, Teaching and Educational Research

The International Journal of Learning, Teaching and Educational Research is an open-access journal which has been established for the disChief Editor Dr. Antonio Silva Sprock, Universidad Central de semination of state-of-the-art knowledge in the Venezuela, Venezuela, Bolivarian Republic of field of education, learning and teaching. IJLTER welcomes research articles from academics, edEditorial Board ucators, teachers, trainers and other practitionProf. Cecilia Junio Sabio ers on all aspects of education to publish high Prof. Judith Serah K. Achoka quality peer-reviewed papers. Papers for publiProf. Mojeed Kolawole Akinsola Dr Jonathan Glazzard cation in the International Journal of Learning, Dr Marius Costel Esi Teaching and Educational Research are selected Dr Katarzyna Peoples through precise peer-review to ensure quality, Dr Christopher David Thompson originality, appropriateness, significance and Dr Arif Sikander readability. Authors are solicited to contribute Dr Jelena Zascerinska to this journal by submitting articles that illusDr Gabor Kiss trate research results, projects, original surveys Dr Trish Julie Rooney Dr Esteban Vázquez-Cano and case studies that describe significant adDr Barry Chametzky vances in the fields of education, training, eDr Giorgio Poletti learning, etc. Authors are invited to submit paDr Chi Man Tsui pers to this journal through the ONLINE submisDr Alexander Franco sion system. Submissions must be original and Dr Habil Beata Stachowiak should not have been published previously or Dr Afsaneh Sharif be under consideration for publication while Dr Ronel Callaghan Dr Haim Shaked being evaluated by IJLTER. Dr Edith Uzoma Umeh Dr Amel Thafer Alshehry Dr Gail Dianna Caruth Dr Menelaos Emmanouel Sarris Dr Anabelie Villa Valdez Dr Özcan Özyurt Assistant Professor Dr Selma Kara Associate Professor Dr Habila Elisha Zuya

VOLUME 15

NUMBER 2

February 2016

Table of Contents The Development and Factor Structure of the Faculty Perceptions of Statistics (FPS) Scale ........................................ 1 Laura Taylor, Kirsten Doehler and Jessalyn Smith Teachers who Attract or Repel: A Glimpse at Student Expectations of their Tertiary-Level Teachers .................... 21 Dr Stephen Joseph The Effects of Goal Type, Learning Interest, and Task Difficulty on Learning English Words ................................ 32 Pengcheng Zhang and Zhe Wang, Olusola Adesope An ICT Approach for Implementing Emerging Technologies for Teaching and Learning in Low Resource Communities: Lessons Learnt from Namibia .................................................................................................................. 47 Shehu M and Jere N.R Descriptive Study on Grade 2 Pupils Relationship Behavior and School Adjustment As Perceived By Teachers: The Case of Jimma Zone, Oromia ...................................................................................................................................... 65 Fisseha Mikre and Nasser Aba-Milki The Magnitude of Teacher Expectation Effects: Differences in Students, Teachers and Contexts ............................ 76 Zheng Li Principles and Practices of ESP Course Designâ&#x20AC;&#x201D;A Case Study of a University of Science and Technology .......... 94 Chin-Ling Lee Escalating Ability to Write Papers: To Make Use of Direct Instruction....................................................................... 106 Ismail Marzuki Studentsâ&#x20AC;&#x2122; Attitudes and English Language Performance in Secondary Schools in Tanzania ................................. 117 Gilman Jackson Nyamubi, Ph.D

International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 1-20, February 2016

The Development and Factor Structure of the Faculty Perceptions of Statistics (FPS) Scale Laura Taylor and Kirsten Doehler Elon University Elon, NC, USA Jessalyn Smith Pacific Metrics Monterey, CA, USA

Abstract. The purpose of this study is to introduce the Faculty Perceptions of Statistics (FPS) scale, report on clusters associated with the inventory, and provide analytical comparisons of sum scores based on demographics. Items on the FPS scale refer to numerous facets of statistics such as the use of statistics in teaching and scholarship. A larger version of the FPS scale was administered online at seven universities and colleges to 747 participants. This research reports on a preliminary validation of the FPS scale to measure attitudes of college faculty towards the statistics discipline based on hierarchical cluster analysis with n=674 participants who completed all items. Seven clusters within the FPS scale were utilized: Comfort, General Teaching, Expectations, Statistical Literacy, Scholarship, Effective Teaching, and Benefits. The Cronbach’s alpha values for the individual clusters ranged from 0.58 to 0.92. This article also highlights numerous results of the data collected by cluster based on participant demographics, such as discipline and previous statistical experience. Keywords: attitudes toward statistics; hierarchical cluster analysis; factor structure; scale development.

1. Introduction In light of the widespread teaching and use of statistics, it is important to understand the perceptions towards statistics held by faculty in other disciplines since they serve as role models to their students. Faculty perceptions and use of statistics could have a significant impact on students’ perceptions and uses of statistics. There is a growing collection of research related to students’ attitudes and perceptions toward the field of statistics, and several inventories exist to measure these student views. Some prominent inventories include: the Survey of Attitudes Toward Statistics (Roberts & Bilderback, 1980); the Attitudes Toward

Statistics Scale (Wise, 1985); the Statistics Anxiety Rating Scale (Cruise, Cash, & Bolton, 1985); the Survey of Attitudes Towards Statistics (Schau, Stevens, Dauphinee, & Del Vecchio, 1995); and the Mathematics and Statistics Perceptions Scale (Cherney & Cooney, 2005). These instruments focus on understanding how statistics is viewed by students, and often include questions related to whether students believe that statistics is useful in daily life. Previous research has led to many important findings on students’ attitudes toward statistics, including an entire special issue of the Statistics Education Research Journal devoted to the topic (Schau, Miller, & Petocz, 2012). Findings related to student attitudes indicate a correlation between student’s attitudes and academic gain (Emmioğlu & Capa-Aydin, 2012). Additionally, Cherney and Cooney (2005) state that there is a significant, positive correlation between statistics attitudes and students’ final grades. These results are important due to the potential for faculty attitudes to impact students’ attitudes toward statistics. Recent research has explored comparative classroom experiments on student attitudes towards statistics. For example, Gundlach et al. (2015) investigated attitudes among students taking a statistical literacy course in traditional, online, and flipped classes. Winquist and Carlson (2014) also looked at the effects of flipped classrooms for introductory statistics, but they considered the impacts a year after instruction and reported significantly higher retention for students in the flipped-classrooms. Ciftci, Karadag, and Akdal (2014) examined the impacts of using computer-based tools in statistics instruction for teacher candidates through a variety of scales to measure student attitudes and anxiety related to statistics. A small research study conducted by Autin, Marchionda, and Bateiha (2014) investigated the effects of a student-centered collaborative-learning class on student attitudes toward statistics and indicated some potential benefits to student-centered collaborative learning. However, Shaughnessy (2007) states ―there has been very little research into […] teachers’ beliefs and attitudes toward statistics‖ (p. 1001) as quoted in Eichler (2010). The only previous research the authors have found on the topic of faculty perceptions toward statistics were the Faculty Attitudes Toward Statistics scale (Hassad & Coxon, 2007) and the Teaching of Introductory Statistics Scale (Hassad, 2011). However, Hassad focused on perceptions of faculty who teach statistics in behavior science programs and/or health programs. Based on the authors’ knowledge, there is no survey which considers attitudes of all faculty towards the discipline of statistics, a field utilized by many other disciplines. Additionally, Hassad’s Teaching of Introductory Statistics Scale focused on pedagogical aspects of teaching statistics, which are not considered in this research. Hassad (2013) has also developed the Attitude Toward Technology Integrations Scale, which measures attitudes of statistics instructors. In addition, Hassad (2015) has surveyed statistics instructors about the extent to which they teach statistical literacy and highlights discrepancies between what is actually taught and what instructors intend to teach. It is necessary to further understand statistics perceptions of faculty, especially faculty within client disciplines. These client faculty are interacting with

students who exit out of introductory statistics and enter their classes to use statistics. Therefore, a symbiotic relationship exists between statistics departments and client disciplines whereby statistics courses prepare students to be successful in their major area of study. Faculty attitudes and perceptions are an important area of research, particularly outside of mathematics and statistics departments, since statistics is widely taught and utilized by faculty across many client disciplines (Sterling, Rosenbaum, & Weinkam, 1995; Carlson, 2002; Switzer & Horton, 2007; Doehler, Taylor, & Smith, 2013). Indeed, Eichler (2010) states that future research should ―investigate the teachers’ attitudes towards statistics in more countries involving more representative samples of ordinary teachers‖ (p. 4). The research presented here considers individuals teaching statistics within many other disciplines. Therefore, it helps to fill a gap in the literature. Since statistics is utilized and taught by faculty in a large number of disciplines, it is imperative to also consider how faculty perceive statistics. If instructors have a poor attitude towards statistics and its usefulness, they could prevent statistics from being a positive experience for their students. Garfield, Hogg, Schau, and Whittinghill (2002) state that ―our courses should attempt to build strong positive attitudes towards statistics […] to increase their chances of using statistics after they leave our courses‖ (p. 3). It seems logical that if this is a goal, then instructors and other individuals who influence students should also have ―strong positive attitudes towards statistics.‖ Zieffler et al. (2008) recognize the need for instructors to help students have a positive learning experience when studying statistics. They also state that learning of statistics could increase if students’ attitudes toward the discipline improved. Therefore, student learning of statistics may increase when positive attitudes towards the discipline are displayed by faculty. Although this likely applies more so to faculty teaching statistics within any discipline, this may also apply to faculty who do not actually teach statistics. For example, if a student taking an introductory statistics class overhears a professor in another discipline saying that doing statistics is too hard for him/her, this could negatively impact the student’s learning. The study presented in this manuscript is of importance to the educational research community since a large portion of academics teach statistical topics, whether it be within a course in a client discipline or in an actual statistics course. Section 2 discusses features of the survey and results of the hierarchical cluster analysis that was performed. Section 3 presents a summary of sum scores for each demographic characteristic as well as discussion of inference based on the demographic categories. Concluding remarks are provided in Section 4.

2. Methodology The Faculty Perceptions of Statistics (FPS) survey items were developed by the authors to be similar in intent to those in the aforementioned student attitude scales. Modifications and adjustments were made to a few items from student attitude scales so that the instructor was the intended audience. Many items were crafted based on characteristics which the authors believed would impact faculty attitudes. Question items in the FPS were intended to cover aspects of

teaching statistics, use of statistics, and statistics in research. A working draft of the initial scale was reviewed by three experts in scale development and two subject matter experts. Additionally, an initial analysis was conducted using the first working draft of the scale. The initial data were analyzed to verify the scale’s psychometric characteristics were within industry standards. The final version of the FPS collected information on attitudes and perceptions of faculty towards statistics. This study was conducted under IRB approval. There were 747 participants in the overall study collected from seven colleges and universities in the United States. Responses were collected from four private schools and three public institutions. Of the 747 responses collected, n=674 individuals completed all 33 Likert scale items (see Table 1) used in the hierarchical cluster analysis (HCA) presented in this paper. All Likert items used in the cluster analysis were on a six-point scale from strongly disagree to strongly agree. Demographic information was also collected related to the participants’ previous statistical coursework, highest degree attained, years of teaching experience, job position, discipline, sex, school type (private or public), and use of statistics in teaching. Table 1: Faculty Perceptions of Statistics Scale with Cluster Identification. Item Label Survey Item Cluster General_H

I feel comfortable interpreting statistical results.

1 – Comfort

Research_B

I feel comfortable reading scholarly articles that use statistical analyses.

1 – Comfort

Research_D

I feel confident advising students using statistical analyses in their research.

1 – Comfort

Teaching_A

Given the opportunity, I think I would like to teach classes that discuss or use statistics.

2 – General Teaching

Teaching_C

It is likely that I will educate students on statistical analyses (hypothesis tests, confidence intervals, regression, etc.) in my classes.

2 – General Teaching

Teaching_D

It is likely that my students will understand statistical analyses after taking my class.

2 – General Teaching

Teaching_E

I would feel comfortable using basic statistical methods in courses that I teach.

2 – General Teaching

Teaching_F

I would feel comfortable using advanced statistical methods in courses that I teach.

2 – General Teaching

Education_A

I expect my students to do well in an introductory statistics course.

3– Expectations

Education_B

I expect introductory statistics courses to be relatively easy for my students.

3– Expectations

Education_C

It is important for my students to understand basic statistics in order to do well in my upper-level undergraduate classes.

3– Expectations

General_A

It is useful to be able to understand basic statistics (poll results, averages in newspaper articles, etc).

4 – Statistical Literacy

General_B

I am confident that I understand basic statistics (poll results, averages in newspaper articles, etc).

4 – Statistical Literacy

General_C

I am confident that I can interpret graphs and charts appropriately.

4 – Statistical Literacy

General_F

I think statistical literacy is an important part of being an informed citizen.

4 – Statistical Literacy

General_G

Statistical literacy is important for my field of study.

4 – Statistical Literacy

General_I

It is useful to be able to carry out statistical procedures or methods.

4 – Statistical Literacy

Research_A

It is likely that I will use statistical techniques when conducting research.

5– Scholarship

Research_C

I find it important to use statistical analyses in my research.

5– Scholarship

Research_E

I feel that using statistical methods makes research papers stronger.

5– Scholarship

Research_F

Articles that use statistical methods are more trustworthy.

5– Scholarship

Research_G

Applying statistical techniques makes my research stronger.

5– Scholarship

Research_H

It is more likely that I can get a scholarly paper published if it includes statistical analyses.

5– Scholarship

Research_I

Statistical interpretations written in lay terms have more impact than those technically written.

5– Scholarship

Teaching_B

It is likely that I will use statistics (poll results, averages, graphs, etc.) in my teaching.

6 – Effective Teaching

Teaching_G

The courses that I teach would be enhanced if I had greater statistical knowledge.

6 – Effective Teaching

Teaching_H

For the classes that I teach, it is more important for students to be able to interpret statistical results than to compute statistics.

6 – Effective Teaching

Education_D

I feel that a student with an understanding of statistics (relative to my field) is more likely to have the independent reasoning/analytical skills needed to succeed in the workplace.

7 – Benefits

Education_E

Students with a better understanding of statistics will have an advantage when applying and interviewing for a job.

7 – Benefits

Education_F

I feel that a student with an understanding of statistics (relative to my field) is more likely to have the independent reasoning/analytical skills needed to succeed in graduate school.

7 – Benefits

Education_G

Students with a better understanding of statistics will have an advantage when applying to graduate school.

7 – Benefits

Education_H

I feel that having some statistical training is important for today's college graduate.

7 – Benefits

General_D

I like using statistical formulas.

DROPPED

dmat hclust (*, "complete")

Teaching_H

Teaching_B

General_G

Figure 1: Final cluster solution based on hierarchical cluster analysis with complete linkage.

Research_I

Teaching_G Research_H

Research_G

Research_E

Research_F

Research_A

Research_C

Education_E

Education_G

Education_H

Teaching_D

Teaching_C

Education_F

Education_D

Teaching_A

Education_C

General_A General_D

General_C

General_I

General_B

General_F Education_B

Research_B

Education_A

Research_D

General_H

Teaching_E

Teaching_F

0.8 0.5

0.6

0.7

Height

0.9

1.0

1.1

1.2

To examine the underlying relationship between the survey items, HCA with complete linkage was used. Clusters were identified using a dendrogram and descriptive statistics. The best solution presented seven unique clusters of items, each having moderate to high reliability. During the initial analysis, one original survey item (General_D) was dropped from the final solution due to lack of fit. Specifically, the item had very little variability among respondents and did not fit with any of the clusters found in the solution. This brought the final FPS scale to 32 items. The sizes of the clusters ranged from three to seven items. The unique traits that underlie each cluster are as follows: (1) comfort with statistics, (2) general statistics in teaching, (3) student expectations with statistics and success in a statistics course, (4) statistical literacy, (5) use of statistics in own research or scholarship, (6) using statistics as part of an effective teaching practice, and (7) benefits of statistics to a student’s training. Note that the cluster information can be found in Table 1 with abbreviated cluster titles. Figure 1 shows the dendrogram for the final solution with the seven clusters or scales. For each of the clusters identified in the analysis, summary statistics are reported in Table 2. There was little variance in the responses on the Comfort, Expectations, and Effective Teaching scales. The highest variances were Dendrogram scales. observed on the General Teaching andCluster Scholarship

Table 2: Sum score summary statistics by cluster.

Cluster/Scale 1—Comfort 2—General Teaching 3—Expectations 4—Statistical Literacy 5—Scholarship 6—Effective Teaching 7—Benefits

N 3

Min 3

Q1 10.0

Median 13.0

Mean 12.0

Q3 14.0

Max 15.0

SD 2.8

5 3

11.3 9.0

17.0 10.0

16.5 10.1

22.0 12.0

25.0 15.0

6.1 2.4

6 7

26.0 24.0

28.5 30.0

27.5 27.7

30.0 33.0

30.0 35.0

3.2 6.2

3 5

10.0 18.0

11.0 21.0

11.0 20.3

13.0 23.0

15.0 25.0

2.6 3.8

Cronbach’s alpha was computed to examine the strength of each cluster. Additionally, to examine the relationship between the clusters, the correlation between each cluster was also calculated. Table 3 shows the reliabilities and correlations between clusters. Note that the reliabilities are in bold along the diagonal. The alpha values indicate that the clusters have moderate to strong reliability, which supports the clusters measuring the same trait. Additionally, the correlations between clusters tend to be in the moderate range which supports the notion that the clusters are measuring unique traits. Note that the most related clusters are Comfort and General Teaching. The most unique pairs of clusters are Comfort and Effective Teaching, Comfort and Expectations, and Expectations and Effective Teaching. Table 3: Cronbach’s alpha (diagonal) for each cluster and the inter-cluster correlations.

Cluster/Scale 1—Comfort 2—General Teaching 3—Expectations 4—Statistical Literacy 5—Scholarship 6—Effective Teaching 7—Benefits

1 0.85 0.78 0.36 0.66 0.56 0.36 0.45

0.92 0.49 0.61 0.54 0.54 0.53

0.58 0.37 0.41 0.36 0.49

0.80 0.53 0.88 0.48 0.45 0.60 0.54 0.60 0.45 0.87

3. Results The following section describes the demographics of the sample used in the cluster analysis. Additionally, to gain a better understanding of the differences in perception of statistics among various demographics, the findings from the cluster analysis were used to determine if there were identifiable differences between any demographic subgroups. This was carried out using simultaneous confidence intervals which were generated using Fisher’s LSD adjustment to control the family-wise type I error rate at 0.05. The following sections highlight some of the more interesting differences detected, but for brevity, all significant differences are not highlighted.

3.1. Demographics There were 674 respondents from seven universities and colleges in the United States who answered all of the original 33 Likert scale items considered. The participant pool was fairly even between females (51%) and males (49%). Approximately 85% of respondents had taken a statistics class. Of these individuals, about 82% had taken their most recent statistics class at the graduate level. The mean and median of the number of years taught by respondents were 13.3 and 10 years, respectively. The corresponding standard deviation was 10.5 years. Respondents came from a variety of levels of academic attainment. There were 69% with a Ph.D., 19% with a Masters degree, 4% with a Professional degree, 1% with a Bachelor’s degree, and 6% of participants indicated some other degree as their highest level of attainment. Presented in Table 4 is the distribution of position type within each academic area for the survey respondents. The two disciplines most represented were STEMS (Science, Technology, Engineering, Mathematics, and Statistics) and Social/Behavioral Science with 21% and 20% of responses, respectively. Additionally, most participants had a professorial position (72%) or nonprofessorial teaching position (21%). Individuals on non-professorial teaching tracks held positions such as lecturer, adjunct, instructor, or similar position. The small number of individuals who selected ―Other‖ as their teaching position tended to identify themselves as professor emeritus, staff, or having multiple positions. Table 4: Demographic distribution of faculty position type within academic area. Assist. Assoc. Full TeachAcademic Area Admin Prof. Prof. Prof. ing Other Total Arts

Business/Mgmt.

Communications

Education

Health/Medicine

110

Humanities

Professional Fields

STEMS Social/Behavioral Sciences Vocational/Technical Fields

139

138

Total

174

172

136

143

674

Almost 31% of respondents indicated that they use statistics or teach statistical methods in their classes ―frequently‖ or ―almost all of the time,‖ while 32% stated that they use statistics occasionally in their teaching. The remaining 37% of respondents reported using statistics ―rarely‖ or ―never‖ in their teaching. A

vast majority of respondents indicated that they were comfortable teaching statistical procedures in their undergraduate courses, with only 12.5% indicating that they were ―neutral‖ or ―not comfortable‖ teaching statistics. Sum scores were calculated for each scale to measure statistics attitudes and were combined to calculate an overall sum score. Table 5 contains summary statistics for average overall sum scores and averages for each of the seven scale sum scores for each demographic category.

No (n=101) Yes (n=573)

104.4 (21.1) 128.7 (18.8)

9.5 (2.9) 12.4 (2.6)

11.4 (5.4) 17.4 (5.7)

9.0 (2.4) 10.3 (2.3)

25.3 (3.4) 27.9 (3.0)

21.5 (7.2) 28.8 (5.3)

9.8 (2.9) 11.2 (2.5)

17.9 (4.3) 20.8 (3.5)

Graduate (n=471) Undergraduate/HS (n=101)

132.4 (15.6) 111.4 (22.3)

12.8 (2.3) 10.3 (3.0)

18.3 (5.3) 13.4 (6.0)

10.5 (2.2) 9.5 (2.5)

28.3 (2.6) 25.9 (3.7)

29.8 (4.4) 24.1 (6.6)

11.6 (2.1) 9.3 (3.2)

21.2 (3.2) 18.9 (4.0)

Bachelor’s (n=9) Masters (n=132) Ph.D. (486) Professional (n=38) Other (n=9)

122.6 (16.6) 116.1 (21.2) 128.2 (20.6) 118.7 (16.0) 117.9 (17.4)

11.3 (2.2) 10.5 (2.9) 12.5 (2.6) 10.2 (2.6) 11.4 (2.2)

15.4 (5.7) 13.5 (6.0) 17.7 (5.7) 12.8 (4.9) 13.6 (5.7)

9.9 (2.3) 9.5 (2.2) 10.3 (2.3) 9.9 (2.5) 10.0 (2.8)

27.1 (2.8) 26.1 (3.9) 28.0 (2.9) 26.3 (3.1) 25.9 (2.8)

28.4 (2.7) 26.5 (5.5) 27.9 (6.5) 28.7 (5.2) 28.2 (5.7)

9.8 (3.8) 10.2 (3.2) 11.3 (2.4) 10.9 (2.4) 8.8 (3.8)

20.6 (3.2) 19.7 (3.7) 20.6 (3.9) 19.9 (2.8) 20.0 (3.5)

(n=199) (n=137) (n=149) (n=107) (n=72)

123.8 (20.7) 124.9 (21.9) 126.0 (21.8) 124.7 (20.1) 129.5 (19.2)

11.6 (2.8) 11.7 (3.0) 12.5 (2.5) 11.9 (2.8) 12.5 (2.9)

15.8 (6.0) 16.4 (6.3) 17.0 (6.0) 16.7 (5.8) 18.0 (5.9)

9.8 (2.3) 10.0 (2.2) 10.1 (2.6) 10.4 (2.2) 10.6 (2.3)

27.3 (3.3) 27.6 (3.0) 27.7 (3.1) 27.2 (3.5) 28.1 (2.6)

28.4 (5.7) 27.6 (6.6) 27.4 (6.5) 27.0 (6.3) 27.8 (5.9)

10.8 (2.8) 11.4 (2.5) 10.9 (2.9) 11.0 (2.4) 11.2 (2.2)

20.1 (3.8) 20.2 (4.2) 20.3 (4.1) 20.4 (3.3) 21.4 (2.7)

Administrator (n=18) Assistant Professor (n=174) Associate Professor (n=172) Professor (n=136) Teaching (n=143) Other (n=31)

126.4 (17.4) 127.3 (19.6) 126.9 (21.0) 128.0 (20.9) 117.3 (22.8) 124.9 (15.0)

12.2 (2.3) 12.1 (2.7) 12.3 (2.6) 12.3 (2.9) 10.9 (3.0) 12.0 (2.6)

16.6 (5.7) 16.9 (5.8) 16.8 (6.0) 17.8 (5.9) 14.4 (6.3) 16.9 (5.6)

10.6 (2.4) 10.0 (2.4) 10.2 (2.3) 10.6 (2.3) 9.7 (2.3) 9.5 (2.4)

27.0 (3.8) 27.9 (2.8) 27.8 (3.4) 28.0 (2.2) 26.2 (3.9) 27.7 (2.3)

27.7 (5.9) 28.7 (6.2) 27.9 (6.2) 27.5 (6.6) 26.4 (5.9) 28.1 (4.8)

11.2 (2.3) 11.2 (2.3) 11.2 (2.5) 11.1 (2.3) 10.3 (3.1) 10.6 (3.1)

21.3 (2.8) 20.4 (3.9) 20.6 (3.7) 20.7 (3.6) 19.6 (4.1) 20.2 (2.6)

Arts (n=29) Business/Manage. (n=59) Communications (n=28) Education (n=65) Health/Medicine (n=110) Humanities (n=76) Professional Fields (n=26) STEMS (n=139) Social/Behav. Sci. (n=138) Vocational/Technical (n=4)

98.6 (18.2) 130.8 (15.7) 119.9 (18.0) 123.6 (17.4) 128.8 (14.3) 98.9 (22.1) 124.3 (19.2) 131.5 (17.8) 134.9 (16.5) 131.3 (7.6)

9.5 (2.7) 12.6 (2.2) 11.9 (2.5) 11.7 (2.6) 11.7 (2.6) 9.2 (3.2) 11.4 (2.6) 12.8 (2.3) 13.2 (2.3) 12.5 (0.6)

10.3 (4.7) 18.3 (5.5) 14.8 (5.5) 15.5 (5.5) 16.3 (5.3) 10.0 (5.0) 15.4 (5.6) 19.4 (4.9) 18.9 (5.3) 17.5 (3.9)

8.2 (2.1) 10.1 (2.1) 8.8 (1.9) 9.8 (2.2) 10.9 (2.0) 8.1 (2.2) 10.3 (2.7) 11.0 (2.0) 10.5 (2.3) 10.0 (1.6)

24.2 (3.7) 28.3 (3.7) 27.4 (2.5) 27.4 (3.4) 27.5 (2.4) 24.6 (3.6) 26.7 (3.6) 28.4 (2.7) 28.7 (2.1) 28.3 (0.5)

21.8 (5.6) 29.2 (4.2) 26.0 (5.6) 27.9 (5.6) 30.3 (3.4) 20.7 (7.2) 28.5 (5.5) 27.9 (6.1) 30.0 (5.0) 29.5 (3.3)

8.0 (2.6) 10.9 (2.3) 11.4 (2.1) 11.4 (2.3) 11.6 (2.4) 9.0 (3.4) 11.1 (2.9) 11.1 (2.4) 11.8 (1.9) 12.3 (1.5)

16.5 (4.3) 21.4 (3.2) 19.7 (3.5) 20.0 (3.0) 20.6 (2.9) 17.2 (4.5) 20.9 (2.7) 20.9 (3.7) 21.8 (3.2) 21.3 (1.5)

Female (n=337) Male (n=326)

123.0 (21.6) 127.3 (20.2)

11.5 (2.9) 12.4 (2.7)

15.4 (6.1) 17.6 (5.8)

10.0 (2.5) 10.2 (2.2)

27.1 (3.4) 28.0 (2.6)

27.9 (6.0) 27.5 (6.4)

11.0 (2.7) 11.0 (2.5)

20.1 (3.8) 20.6 (3.7)

Private (n=250) Public (n=424)

122.6 (24.3) 126.6 (18.7)

11.6 (3.1) 12.2 (2.6)

16.4 (6.6) 16.6 (5.7)

10.2 (2.4) 10.1 (2.3)

27.3 (3.4) 27.6 (3.1)

26.0 (7.0) 28.7 (5.4)

11.0 (2.6) 11.0 (2.7)

20.2 (4.0) 20.4 (3.6)

Almost all of the time (n=55) Frequently (n=152) Occasionally (n=218) Rarely (n=168) Never (n=81)

145.2 (7.0) 139.8 (13.8) 127.7 (14.8) 114.9 (18.3) 98.0 (18.9)

14.3 (1.3) 13.5 (1.9) 12.4 (2.1) 10.6 (2.9) 8.9 (2.7)

23.7 (1.8) 21.3 (3.8) 17.0 (4.6) 12.8 (4.5) 9.1 (4.1)

11.3 (1.9) 11.2 (2.1) 10.2 (2.0) 9.4 (2.5) 8.3 (2.2)

29.6 (0.7) 28.8 (3.1) 28.0 (2.2) 26.5 (3.2) 24.4 (3.7)

30.8 (3.5) 30.4 (4.7) 28.5 (5.0) 25.9 (6.3) 22.1 (7.4)

12.4 (1.9) 12.3 (2.0) 11.4 (2.1) 10.3 (2.4) 7.8 (2.9)

23.1 (2.4) 22.3 (3.3) 20.2 (3.3) 19.3 (3.6) 17.5 (4.1)

7– Benefits

6– Effective Teaching

2– General Teaching

5– Scholarship

1– Comfort

4– Statistical Literacy

Overall

3– Expectations

Table 5: Summary statistics of sum scores for major demographics reported as mean (standard deviation).

Previous statistics coursework

Most recent statistics coursework

Highest Degree

Teaching Experience 0-5 6-10 11-19 20-29 30+ Position

Discipline

Sex

School type

Use of Statistics

3.2. Previous Statistics Coursework Boxplots of sum scores for respondents based on the indicator variable of previous statistics coursework is shown in Figures 2 and 3. Overall there was a significant difference between responses of individuals who have taken a statistics class and those who have not (F1,672 = 138.8, p < 0.0001). In particular, respondents who had taken a statistics class scored significantly higher overall and on all scales (higher on average by 24.3, 2.9, 6.0, 1.3, 2.6, 7.3, 1.4, and 2.9, respectively for overall and scales 1–7) based on Fisher’s LSD adjusted simultaneous pairwise confidence intervals. There was a significant difference between those that had taken their most recent statistics course at the graduate level and those who had taken their most recent statistics course at the undergraduate or high school level (F1,570 = 127.2, p < 0.0001). In particular, respondents who had taken their most recent class at the graduate level scored significantly higher overall and on all scales than individuals who took their most recent statistics class as an undergraduate or high school student (higher on average by 21.0, 2.5, 4.8, 0.9, 2.4, 5.7, 2.3, and 2.3, respectively for overall and scales 1–7).

Figure 2: Sum scores based on previous statistics course (No, Yes).

Figure 3: Sum scores based on most recent statistics coursework (Graduate, Undergraduate/HS).

3.3. Highest Degree Boxplots of sum scores for respondents based on highest degree are shown in Figure 4. Differences in overall average scores based on highest degree were detected (F4,669 = 12.4, p < 0.0001) with a Ph.D. yielding a significantly higher overall average score than those with a Professional degree, Masters degree, or ©2016 The authors and IJLTER.ORG. All rights reserved.

―Other‖ degree (higher on average by 8.7, 12.6, and 12.2, respectively). While there was no significant difference detected between overall scores for those with a Ph.D. compared to a Bachelor’s degree, it is worthwhile to note that the sample size for Bachelor’s degree was nine. It is also of interest to note that there are no significant differences detected between Bachelor’s degrees and any other degree overall or on any scale. Individuals with a Ph.D. degree scored significantly higher than individuals with a Masters degree across all scales (higher on average by 2.1, 4.4, 0.7, 1.9, 1.4, 1.2, and 1.0, respectively for scales 1– 7). Additionally, in all scales except Expectations and Scholarship, respondents with a Ph.D. scored significantly higher than individuals who selected ―Other‖ for their highest degree (higher on average by 2.1, 4.7, 1.8, 1.3, and 1.3, respectively for scales 1–2, 4, and 6–7).

Figure 4: Sum scores based on highest degree (Bachelor’s, Masters, Ph.D., Professional Degree, Other).

3.4. Teaching Experience Years of teaching experience were categorized into the following categories: 0-5, 6-10, 11-19, 20-29, and 30 or more years. Figure 5 shows boxplots of sum scores for respondents based on the years of teaching category. No significant differences in overall scores based on teaching experience were detected (F4,659 = 1.0, p =0.3821). The Comfort scale was the only scale with significant differences detected based on teaching experience (F4,659 = 2.8, p = 0.0251). However, there were no meaningful patterns in the pairwise differences of average sum scores on the Comfort scale.

Figure 5: Sum scores based on teaching experience (0-5, 6-10, 11-19, 20-29, 30+ years).

3.5. Position Figure 6 provides boxplots of sum scores for position type. There was a difference detected in the overall average score based on position type (F5,668 = 5.3, p < 0.0001). Full professors, associate professors, and assistant professors scored higher overall than individuals on non-professorial teaching tracks by 10.7, 9.6, and 10.0 points, respectively, on average. Similarly, full professors, associate professors, and assistant professors scored significantly higher than individuals in non-professorial teaching positions for the Comfort, General Teaching, Statistical Literacy, and Effective Teaching scales. On the Expectations scale, full professors scored significantly higher on average than assistant professors, individuals in non-professorial teaching positions, and individuals in the â&#x20AC;&#x2022;Otherâ&#x20AC;&#x2013; category by 0.5, 0.9, and 1.1 points, respectively. On the Expectations, Scholarship, and Benefits scales, associate professors scored significantly higher on average than individuals in non-professorial teaching positions, by 0.5, 1.5, and 1.0 points, respectively. Note that among the assistant, associate, and full professors, the only significant difference detected was a higher score on the Expectations scale for full professors compared to assistant professors, with an average difference of 0.5 points.

Figure 6: Sum scores based on position (Administrator, Assistant Professor, Associate Professor, Professor, Teaching, Other).

3.6. Discipline Participants were asked to identify their discipline from one of the following fields: Arts, Business/Management, Communications, Education, Health/Medicine, Humanities, Professional Fields, STEMS, Social/Behavioral Sciences, and Vocational/Technical Fields. Boxplots of overall sum scores by discipline are given in Figure 7 and for each scale in Figure 8. All comparisons were made for the overall sum scores and the seven scale sum scores among all disciplines with the exception of Vocational/Technical Fields which had only four respondents. There was a difference in overall scores detected based on discipline (F8,661 = 39.5, p < 0.0001). As seen in Table 5, the lowest average sum score overall and for each of the clusters was associated with either the Arts or Humanities. The highest overall sum score was attributed to the Social/Behavioral Sciences, which also yielded the highest average sum score in four of the scales: Comfort, Statistical Literacy, Effective Teaching, and Benefits scales. The highest average sum score for the

General Teaching and Expectations scales were associated with STEMS disciplines. Health/Medicine had the highest average sum score on the Scholarship scale. In general, fewer differences were detected on the Effective Teaching scale, and the most differences were detected on the General Teaching scale. Each discipline was compared with the remaining eight disciplines across the seven scales and across overall sum scores for a total of 64 pairwise comparisons. Professional Fields had the least number of significant pairwise differences detected among these comparisons with a total of 22 significant differences detected. Both Arts and Humanities had the most significant pairwise differences when compared to other disciplines with a total number of 52 significant pairwise differences detected. There were six or seven significant differences detected on each scale and in the overall sum scores for both Arts and Humanities. The only pairs of disciplines that were not significantly different from each other overall or across any scales were (1) Arts and Humanities and (2) Health/Medicine and Professional Fields. The following pairs of disciplines were significantly different from each other in overall sum scores and on every scale were Arts with (1) Business/Management, (2) Education, (3) Health/Medicine, (4) STEMS, and (5) Social/Behavioral Science and Humanities with the same disciplines as Arts.

Figure 7: Overall sum scores based on discipline (Arts, Business/Management, Communications, Education, Health/Medicine, Humanities, Professional fields, STEMS, Social/Behavioral Sciences, Vocational/Technical fields).

(a) Comfort Sum Scores

(b) General Teaching Sum Scores

(d) Statistical Literacy Sum Scores

(e) Scholarship Sum Scores

(f) Effective Teaching Sum Scores

(g) Benefits Sum Scores Figure 8: Boxplots of sum scores for scale by discipline ((Arts, Business/Management, Communications, Education, Health/Medicine, Humanities, Professional fields, STEMS, Social/Behavioral Sciences, Vocational/Technical fields).

3.7. Sex Boxplots of sum scores by sex are given in Figure 9. There was a difference in average sum scores between males and females (F1,661 = 7.1, p = 0.0080) with male respondents scoring significantly higher overall than female respondents by between 1.1 and 7.5 points. In addition, scores on the Comfort, General Teaching, and Statistical Literacy scales were also significantly higher for males (higher on average by 0.9, 2.2, and 0.9, respectively for scales 1â&#x20AC;&#x201C;2 and 4). The Expectations, Scholarship, Effective Teaching, and Benefits scales showed no significant differences between females and males.

Figure 9: Sum scores based on sex (Female, Male).

3.8. School Type Figure 10 shows overall sum scores based on school type. Average overall score was significantly different (F1,672 = 5.7, p = 0.0168) with individuals from public institutions scoring significantly higher than those at private institutions by between 0.7 and 7.3 points. Similarly, scores on the Comfort and Scholarship scales were also significantly higher at public institutions (higher on average by 0.6 and 2.7, respectively). No other significant differences were detected between scale scores based on school type.

Figure 10: Sum scores based on school type (Private, Public).

3.9. Use of Statistics Each respondent was asked to identify how often they use statistics or teach statistical methods in their classes. Associated boxplots of sum scores are located in Figure 11. There was a significant difference in the average overall ÂŠ2016 The authors and IJLTER.ORG. All rights reserved.

sum scores based on use of statistics (F4,669 = 136.8, p < 0.0001). Specifically, average sum scores increased as the frequency of statistics usage increased from ―Never,‖ ―Rarely,‖ ―Occasionally,‖ ―Frequently,‖ and ―Almost all of the time.‖ The average overall sum scores were 98.0, 114.9, 127.7, 139.8, and 145.2, respectively. Significant pairwise differences were detected between all use of statistics response categories in overall sum scores and in the sum scores for the Comfort and General Teaching scales. For the remaining scales, all pairwise differences of sum scores were significantly different with the exception of the ―Almost all of the time‖ and ―Frequently‖ response categories, for which no significant differences were detected.

Figure 11: Sum scores based on the use of statistics (Almost all of the time, Frequently, Occasionally, Rarely, Never).

4. Discussion Not surprisingly, a comparison of sum scores based on demographics indicated that the presence of previous statistics coursework is an indicator of the importance for which faculty have towards the discipline of statistics. This appeared higher with graduate level statistical coursework compared to lower levels of coursework in statistics. In addition, the level of academic achievement held some importance on the sum scores overall and across scales with Ph.D. respondents scoring consistently and significantly higher than individuals with a Masters degree. The type of position provided some indication on sum scores. In particular, individuals on the professorial track tended to have higher scores. Scores varied greatly across disciplines with Humanities and Arts having scores significantly lower than other fields. Male respondents had significantly higher scores on some but not all scales. Based on the results, private colleges and universities have a significantly higher overall sum score. However, these results may be associated with whether an institution is considered to be a Research I, liberal arts, or other type of school. As expected, a higher frequency of teaching statistics is associated with a significantly higher average statistics attitude scores. Based on the results, there was not a relationship detected between overall sum scores and years of teaching experience. Initially this was somewhat surprising, since it is likely that more experience teaching is positively correlated with more exposure to statistics. However, with statistics being a relatively new and rapidly growing discipline, it is possible that younger faculty and instructors utilize statistics

more and therefore also have positive attitudes towards the discipline and its usefulness. While the current study includes responses from seven colleges and universities, the responses were collected through online surveys for convenience. As is the norm, participation was voluntarily. Although this type of sampling method is common in many studies, it is possible that respondents were more likely to be interested in statistics, resulting in more positive attitudes. In an effort to reduce possible biases and encourage more individuals to respond, participants at six of the seven schools were eligible to enter a drawing to win one of multiple $20 gift cards that were available. The number of responses obtained also appeared to be related to how the email with the survey link was distributed. For example, at some schools the survey was sent by a contact individual, while at other schools the survey link was sent out via a forwarded email. In general larger schools tended to yield more responses. Varying response rates among institutions could have impacted the demographic characteristics of our sample.

5. Conclusion Little to no research exists measuring the attitudes of faculty across all disciplines towards statistics. The Faculty Perceptions of Statistics (FPS) scale introduces a survey of 32 Likert scale items to measure these attitudes. Based on the results of the hierarchical cluster analysis, it is clear that there are some underlying constructs related to the views that faculty or academic department members have towards the use and importance of statistics. The analysis indicates seven scales: Comfort, General Teaching, Expectations, Statistical Literacy, Scholarship, Effective Teaching, and Benefits. This study is an initial exploration into the area of faculty attitudes and shows promise with Cronbach’s alpha values ranging from 0.58 to 0.92 for the different clusters identified. Based on these results, differences in cluster sum scores were detected among demographic groups. Many of the differences were not surprising. For example, having statistical experience tended to lead to increases in sum scores. There was a lot of variability in sum scores among the disciplines, with Arts and Humanities having the lowest sum scores both overall and for all clusters. Somewhat surprisingly, there did not appear to be a relationship between years taught and attitudes towards statistics based on sum scores. The FPS instrument would benefit from further refinement, and additionally, a cross-validation study and invariance testing should be conducted in order to see if the clusters found are generalizable. It would also be beneficial to administer the FPS scale survey across a wider variety of institutions such as community colleges. The FPS scale and the findings presented in this paper are an initial step into examining the interwoven attitudes of faculty and students. Previous literature indicates a strong relationship between students’ attitudes and academic success in statistics courses (Emmioğlu & Capa-Aydin, 2012; Cherney & Cooney, 2005).

Based on this, more research should be conducted to explore the relationship between faculty attitudes towards statistics and students’ attitudes.

References Autin, M. Marchionda, H. & Bateiha, S. (2014). Attitude Adjustment in Introductory Statistics. In proceedings of the 41th Annual Meeting of the Research Council on Mathematics Learning, San Antonio, Texas, 80-88. Carlson, B. (2002). Preparing Workers for the 21st Century: The Importance of Statistical Competencies. In proceedings of the International Conference on Teaching Statistics (ICOTS-6), Cape Town, South Africa, 1-6. Ciftci, S. K., Karadag, E., & Akdal, P. (2014). Instruction of Statistics via Computer-Based Tools: Effects on Statistics’ Anxiety, Attitude, and Achievement. Journal of Educational Computing Research, 50(1), 119-133. Cruise, J. R., Cash, R. W., & Bolton, L. D. (1985). Development and validation of an instrument to measure statistical anxiety. In proceedings of the American Statistical Association, Section on Statistical Education, Las Vegas, 92-97. Cherney, I. D. & Cooney, R. R. (2005). Predicting student performance in a statistics course using the Mathematics and Statistics Perception Scale (MPSP). Transactions of the Nebraska Academy of Sciences, 30, 1-8. Doehler, K., Taylor, L., & Smith, J. (2013). A Study of Faculty Views of Statistics and Student Preparation Beyond an Introductory Class. Journal of Statistics Education, 21(1). Retrieved from http://www.amstat.org/publications/jse/v21n1/doehler.pdf Eichler, A. (2010). The Transformation Process from Written Curricula to Students’ Learning. In proceedings of the International Conference on Teaching Statistics 8 (ICOTS8), Ljubljana, Slovenia. Voorburg, The Netherlands. Retrieved from http://icots.info/8/cd/pdfs/invited/ICOTS8_8E3_EICHLER.pdf Emmioğlu, E. & Capa-Aydin, Y. (2012). Attitudes and achievement in statistics: A metaanalysis study. Statistics Education Research Journal, 11(2), 95-102. Retrieved from http://iase-web.org/documents/SERJ/SERJ11(2)_Emmioglu.pdf Garfield, J., Hogg, B., Schau, C., & Whittinghill, D. (2002). First Courses in Statistical Science: The Status of Educational Reform Efforts. Journal of Statistics Education, 10(2). Retrieved from http://ww.amstat.org/publications/jse/v10n2/garfield.html Gundlach, E., Richards, K. A., Nelson, D. & Levesque-Bristol, C. (2015). A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Webaugmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class. Journal of Statistics Education, 23(1). Retrieved from http://www.amstat.org/publications/jse/v23n1/gundlach.pdf Hassad, R. A. & Coxon, A. P. M. (2007). Development and Initial Validation of a Scale to Measure Instructors’ Attitudes toward Concept-Based Teaching of Introductory Statistics in the Health and Behavioral Sciences. In proceedings of the International Statistical Institute, 56th Session, Lisbn, Portugal. Retrieved from http://files.eric.ed.gov/fulltext/ED506520.pdf Hassad, R. A. (2011). Constructivist and Behaviorist Approaches: Development and Initial Evaluation of a Teaching Practice Scale for Introductory Statistics at the College Level, Numeracy, 4(2). Retrieved from http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=1057&context=nu meracy Hassad, R. A. (2013). Faculty Attitude towards Technology-Assisted Instruction for

Introductory Statistics in the Context of Education Reform. Technology Innovations in Statistics Education, 7(2). Hassad, R. A. (2015). Variability in the Teaching of Statistical Literacy: A Case of Pedagogical Dissonance. In proceedings of the Satellite Conference of the International Association for Statistical Education (IASE), Rio de Janeiro. Roberts, D. M. & Bilderback, E. W. (1980). Reliability and Validity of Statistics Attitude Survey. Educational and Psychological Measurement, 40(1), 235-238. Schau, C., Miller, M., & Petocz, P. (Eds.). (2012). Research on Attitudes Towards Statistics [Special Issue]. Statistics Education Research Journal, 11(2). Schau, C., Stevens, J., Dauphinee, T. L, & Del Vecchio, A. (1995). The development and validation of the Survey of Attitudes Toward Statistics. Educational and Psychological Measurement, 55(5). 868-875. Shaughnessy, J. M. (2007). Research on statistics learning and reasoning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 9571010). Charlotte, NC: Information Age Publishing. Sterling, T. D., Rosenbaum, W. L., & Weinkam, J. J. (1995). Publication Decisions Revisited: The Effect of the Outcome of Statistical Tests on the Decision to Publish and Vice Versa. The American Statistician, 49(1), 108-112. Switzer, S. S. & Horton, N. J. (2007). What Your Doctor Should Know about Statistics (but Perhaps Doesn’t…). CHANCE, 20(1), 17-21. Winquist, J. R. & Carlson, K. A. (2014) Flipped Statistics Class Results: Better Performance Than Lecture Over One Year Later. Journal of Statistics Education, 22(3). Retrieved from http://www.amstat.org/publications/jse/v22n3/watkins.pdf Wise, S. L. (1985). The development and validation of a scale measuring attitudes toward statistics. Educational and Psychological Measurement, 45(2), 401 – 405. Zieffler, A., Garfield, J., Alt, S., Dupuis, D., Holleque, K., & Chang, B. (2008). What Does Research Suggest About the Teaching and Learning of Introductory Statistics at the College Level? A Review of the Literature. Journal of Statistics Education, 16(2). Retrieved from www.amstat.org/publications/jse/v16n2/zieffler.html

International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 21-31, February 2016

Teachers who Attract or Repel: A Glimpse at Student Expectations of their Tertiary-Level Teachers Dr Stephen Joseph Centre for Education Programmes, The University of Trinidad and Tobago Valsayn Campus, Old Southern Main Road, Curepe, Trinidad and Tobago

Abstract. This study examined student expectations of their tertiarylevel teachers, highlighting specific teacher characteristics that either attract or turn off students from their professors. Four hundred and one (401) students were randomly selected from three teacher education campuses in the north and south of Trinidad as well as Tobago. Findings of the study revealed that students generally had high expectations of their teachers on two levels: (i) pedagogical competence and (ii) discipline competence. Findings also revealed that the three teacher characteristics that attract students to their professors were caring for the welfare of students; professionalism; and teaching style. Conversely, students listed unprofessionalism; teacher aggressive attitude; and lack of concern for students as things that repel them from their professors.

Keywords: student expectations; tertiary-level teachers; teacher characteristics

Introduction University students generally welcome the opportunity to choose their lecturers. However, some professors become self-conscious when only a few individuals select their courses while the majority of students gravitate to other instructors. Increasingly, students are expecting more of their tertiary-level teachers in terms of pedagogical competence, discipline competence, and endearing personal characteristics. In their study on the best and worst university instructors, Fortson and Brown (1998) found that the best instructors were those who used a variety of teaching methods and good course organization. Poor course organization was the characteristic that most influenced studentsâ&#x20AC;&#x2122; choice of their worst instructors. Other studies identified favourite teachers as those who possessed sound content knowledge and pedagogical skills as opposed to professors who ÂŠ2016 The author and IJLTER.ORG. All rights reserved.

focussed more on research rather than teaching (Tam, Heng, & Jiang, 2009). Similar studies identified effective communication, enthusiasm, well-organized lessons, and sound knowledge as top qualities of effective university teachers (Malik & Bashir, 2015; Singh, Pai, Sinha, Kaur, Soe & Barua, 2013; AlMohaimeed, 2015). Student conceptions of the ideal or most effective teacher fall into three major categories: (1) knowledge of the subject taught (2) personal qualities (3) knowledge of teaching and learning (Arnon & Reichel, 2007; Crawford & Bradshaw, 1968; Witcher, Onwuegbuzie & Minor, 2001; Douna, Kyridis, Zagkos, Ziontaki, & Pandis, 2015; Obermiller, Ruppert, & Atwood, 2012; Slate, La Prairie, Schulte, & Onwuegbuzie, 2011; Epting, Zinn, Buskist & Buskist, 2004; Korte, Lavin & Davies, 2013). Studies have shown that excellent professors also tend to exhibit specific personal characteristics beyond instructional practices. Gurung and Vespia (2007) posit that “professors should not think just about preparation for lectures but also about preparation for being in the classroom” (p.9). Findings of these studies also revealed that students generally enjoyed the teaching and learning process better when lecturers were friendly and accommodating, interacted well with students, and paid attention to personal grooming. McLean (2001) concurred that personal qualities were more important to students than other technical aspects of the job such as well-organized lesson plans and lectures. Students also expect their instructors to have a good sense of humour, maintain interesting class sessions, as well as demonstrate caring and concern for students (Fortson & Brown, 1998; Strage, 2008; Feldman, 1998; Goa & Liu, 2013). Since the education process can also be considered as a social process, students expect their instructors to go beyond traditional roles of lecturing to embrace more social aspects of learning (Giroux, 1988). Therefore, more is demanded of the teacher’s time outside of the formal classroom setting for consultation and feedback on students’ performance. Although there is a proliferation of studies on the ideal professor conducted Europe, North America, and to a lesser extent Asia, not much has been done Trinidad and Tobago and the Caribbean to investigate student perceptions their tertiary-level teachers. This current study seeks to expand the discourse the Caribbean region.

in in of to

Purpose of the study The purpose of this study was to examine what students expect of their university teachers and what specific teacher characteristics attract or turn off students from the teaching/learning process. Three research questions served to focus this investigation: 1. What are students’ expectations of their tertiary-level teachers? 2. What teacher characteristics attract students most to their tertiary-level teachers? ©2016 The author and IJLTER.ORG. All rights reserved.

3. What teacher characteristics turn off students most from their tertiarylevel teachers?

Methodology Participants A random sample of 401 students was selected to participate in the study. These respondents were both full-time and part-time students enrolled in the University of Trinidad and Tobago Bachelor of Education programme at three campuses located in the northern and southern parts of Trinidad and well as Tobago. Instrument This study utilized a survey instrument with 20 items covering three objectives arising from the research questions outlined above. Using a 5-point Likert-type scale, respondents were required to express their opinions regarding what they expect of their tertiary-level teachers. The instrument was pilot-tested and feedback from that activity was used to improve the instrument before formally distributing the questionnaires to the research sample. Cronbachâ&#x20AC;&#x2122;s alpha was used to measure internal consistency or reliability for 6 of the items used in the Likert scale. The result was .847, which indicates a high level of internal consistency for the items used in the scale. Procedure and Analyses As part of the survey, participants were asked share their expectations of their tertiary-level teachers. Frequencies and descriptive statistics were conducted to provide information about the sample used in the study. Frequency tables were also developed for recording and tabulating demographic responses with the aid of the Statistical Package for the Social Sciences (SPSS) software. The demographic responses included questions related to gender, degree programme, status (part-time or full-time) and level (Year I, II, III, or IV).

Results Four hundred and one (401) undergraduate students participated in a survey which required them to share their expectations of their professors. These participants were located in the north (40.1%) and south (42.4%) of Trinidad as well as Tobago (17.5%). As shown in Table 1, the majority of participants, 72.3%, (n= 290) were females, while 27.7%, (n= 111) were males. Frequency analysis of the data also revealed that the majority of the respondents, 64.3% (n=258) were part-time students, while 32.4% (n=130) engaged in full-time studies. Table 1 also shows a distribution of students according to the year of study in the undergraduate programme.

Table 1. Demographic Data on Participants Demographic Geographic Location North South Tobago Total Gender Male Female Status Part-time Full-time Missing

N (%) 161 (40.1) 170 (42.4) 70 (17.5) 401 (100) 111 (27.7) 290 (72.3) 130 (32.4) 258 (64.3) 13 (3)

Level Year I Year II Year III Year IV Missing

56 (14) 131 (32.7) 115 (28.7) 85 (21.2) 14 (3.5)

Student responses to the survey questionnaire were grouped in the following three categories: (1) student pedagogical expectations (2) discipline and pedagogical competence (3) teacher characteristics. As shown in Table 2, all of the respondents, irrespective of their level or status, indicated very high pedagogical expectations of their professors. They all expected their professors to find out how they learn best; use appropriate teaching/learning methods; and set high standards for teaching and learning. Table 2. Student Pedagogical Expectations Pedagogical Expectations Find out how I learn best

Use of appropriate teaching/learni ng methods

Set high standards for teaching and learning

46/56

53/56

55/56

105/131

125/131

Year III

100/115

111/115

Year IV

71/85

79/85

77/85

Total

322/387

368/387

Status Part-time Full-time Total

213/258 109/130 322/388

246/258 123/130 369/388

246/258 125/130 371/388

Demographic Level Year I Year II

In addition to having high pedagogical expectations of their teachers, participants of the study also expected their professors to keep up-to-date with developments in their specific disciplines; use appropriate assessment methods; as well as provide prompt feedback on their assignments. Table 3 provides information on student expectations about their professors’ discipline competence. As shown in Table 3, 97% (n=374) of the respondents indicated that their professors should always keep up-to-date with content knowledge in their specific fields, while 98% (n=378) of the participants felt that their teachers should explore appropriate assessment measures to evaluate student learning, and 95% (n=366) of the respondents required prompt feedback from their professors on their class assignments. Review of the data revealed a high level of consistency in the responses among participants regardless of their level or status. All participants had high expectations regarding teachers’ competence in their various subject domains. Table 3. Discipline Competence Discipline Competence I except my teacher to always keep upto-date with content knowledge

I expect my teacher to use appropriate assessment methods

I expect my teacher to provide prompt feedback on my

54/56

55/56

54/56

127/131

125/131

Year III

114/115

111/115

Year IV

79/85

82/85

76/85

Total

374/387

378/387

366/387

Status Part-time Full-time Total

250/258 124/130 374/388

251/258 128/130 379/388

243/257 123/130 366/388

Demographic Level Year I Year II

assignments

Participants were asked to report their level of confidence in their professors’ ability to effectively teach concepts; conduct fair assessment; and model what good teaching is all about. These responses were based on a table which indicated 0 – 30% as no confidence; 40 – 80% as moderate confidence; and 90-100% as complete confidence. As shown in Table 4a, the majority of participants (67.7%) reported moderate confidence in their teacher’s ability to effectively teach concepts, with 19.3% indicating no confidence at all, and 13.5% reporting complete confidence in their professors’ ability to teach concepts effectively. ©2016 The author and IJLTER.ORG. All rights reserved.

Table 4a. Pedagogical Competence

Level

Teachers’ ability to effectively teach concepts No Moderate Complete Total Confidence Confidence confidence 12 32 11 55 24 88 14 126 16 77 18 111 20 57 6 83 72 254 49 375

Year I Year II Year III Year IV

Total Status Part-time Full-time Total

61 12

154 99

34 17

249 128

253

377

Participants indicated similar responses when asked about their teachers’ ability conduct fair assessment. The data presented in Table 4b show that 64.5% of the respondents had moderate confidence, while 19.3% indicated no confidence, and 16.3% said that they had complete confidence in their teachers’ ability to conduct fair assessment of their work. Table 4b. Pedagogical Competence

Level

Year I Year II Year III Year IV

Total

No Confidence 10 31 17 15

Teachers’ ability to conduct fair assessment Moderate Complete Total Confidence Confidence 37 8 55 75 22 128 50 24 111 62 7 84

244

378

53 20

154 91

44 18

251 129

245

380

Status Part-time Full-time Total

When asked about their professors’ ability to effectively model what good teaching is all about, only 12.6% indicated complete confidence, while the majority (64.6%) reported moderate confidence and 23.2% indicated that they had no confidence at all in their professors’ ability to act as good models of classroom teaching. This information is illustrated in Table 4c below.

Table 4c. Pedagogical Competence

Level

Year I Year II Year III Year IV

Total

Teachersâ&#x20AC;&#x2122; ability to effectively model what good teaching is all about No Moderate Complete Total Confidence Confidence Confidence 14 34 7 55 37 79 13 129 18 72 21 111 19 57 7 83 88 242 48 378

Status Part-time Full-time Total

66 21

156 89

27 20

249 130

245

379

Participants were asked to rank the most important characteristics they expect professors to possess in the teaching/learning context. As shown in Table 5, participants listed professionalism; dedication to teaching; preparedness for class; strong ethical values; and caring/understanding as the top five characteristics they expect teachers to possess. The five least important characteristics were charisma; sociability; ability to use technology; well-dressed; and enthusiasm. Table 5. Teacher Characteristics in order of importance 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

Professionalism Dedicated to teaching Always prepared for class Strong ethical values Caring/understanding Positive attitude Engage students in class Ability to relate well to students Fairness in assessments Fun/interesting Enthusiasm Well-dressed Ability to use technology Sociability Charisma

Participants of the study were also to list three things that either attracted them or turned them off from their professors. As shown in Table 6, 44.2% of the respondents indicated caring as the number one quality that attracted them to ÂŠ2016 The author and IJLTER.ORG. All rights reserved.

their teachers; 36.2% indicated professionalism; and 33.7% listed teaching style. Unprofessionalism was the major turn off as reported by 41.1% of the respondents; while 40.7% of the participants identified aggressive behaviour; and 27.7% listed lack of concern for students as other characteristics that they disliked most in professors. Table 6. Things that attract or repel students from their professors Things that attract 1. Caring 2. Professionalism 3. Teaching style

Things that repel 1. Unprofessionalism 2. Aggressive attitude 3. Lack of concern for students

The final two questions in the survey explored how students regarded teachers who challenged them to think critically as opposed to those who graded easily. Analysis of the data revealed that 85% of the respondents showed preference to those teachers who challenged them to think critically. Only 15% of the participants indicated preference for teachers who graded easily.

Discussion This study examined student expectations of their tertiary-level teachers on three levels: (i) pedagogical competence; (ii) discipline competence; and (iii) teacher characteristics. Pedagogical competence The majority of participants in the study, irrespective of level or status, indicated high expectations of their professors in terms of their ability to recognize varying learning preferences among students. As such, participants expect teachers to set high standards while using appropriate teaching/learning strategies to maximize the learning potential in each student. These expectations matched those in Fortson and Brown’s (1998) study which showed that the best

instructors were those who used a variety of teaching methods. Participants of the study expressed moderate confidence in their professors’ ability to teach concepts effectively. Only 13.5% reported complete confidence, while 19.3% indicated that they had no confidence at all in their professors’ ability to effectively teach concepts. These results suggest that professors should pay closer attention to concept teaching especially in a teacher education setting where effective concept teaching is critical to student success on practicum or field teaching. Studies conducted by Hande, Kamath and D’Souza (2014) concluded that students perceive teachers as effective when they are able to clarify difficult concepts, and make learning fun and interesting. Student perception of their teachers’ ability to conduct fair assessment should also be noted as a matter of concern. While the majority of respondents (64.5%) indicated moderate confidence, 19.3% stated that they had no confidence in their ©2016 The author and IJLTER.ORG. All rights reserved.

professors’ ability to conduct fair assessment of student learning. This perception seems consistent with student rating of teacher characteristics, where fairness in assessments was ranked 9th on a scale of 1-15 as shown in Table 5. Modelling good classroom teaching to students is an important objective for professors operating in a teacher education setting. It means, therefore, that professors should not only be concerned with content delivery, but also how different students interact with the content taught in the classroom. Results of the study revealed that almost one quarter of the participants (23.2%) had no confidence in their professors’ ability to act as good models of classroom teaching. And while 64.6% of the participants reported moderate confidence in their teachers’ ability to model good teaching, professors in a teacher education context should not be comforted by this. These results suggest the need for greater effort on the part of professors to bolster student confidence in their teachers’ pedagogical competence. If prospective teachers are expected to demonstrate effective teaching skills in the practicum classroom, then professors should feel a sense of responsibility to model what good teaching looks like. Discipline competence Results of the study revealed that the majority of participants (97%) expect their professors to always keep abreast with the latest developments in their field. Students also expect their teachers to use appropriate assessment methods as well as provide prompt feedback on student assignments. These findings are consistent with other studies that emphasize the importance of subject mastery as an indicator of teacher competence (Arnon & Reichel, 2007; Roberts, 1981). Teacher characteristics Participants of the study listed the five most important teacher characteristics as professionalism; dedication to teaching; preparedness for class; strong ethical values; and caring/understanding. The five least important qualities were charisma; sociability; ability to use technology; well-dressed; and enthusiasm. Student responses were consistent when asked to indicate the things that either attract or repel students from their professors. Again we see teacher professionalism and caring emerging as important characteristics that attract students to their tertiary-level teachers. These findings are somewhat different from similar studies conducted by Gurung and Vespia (2007), and McLean (2001) who found that students learned more and liked the class better when teachers were well-dressed, good-looking and approachable. In this study, welldressed teachers were not as important to students as those who demonstrated professionalism and caring for the welfare of students.

Concluding Comments Professors generally set high standards for their students in terms of critical thinking and problem-solving skills; classroom management and leadership skills as well as reflective teaching skills. In like manner, students have high expectations of their tertiary-level teachers. This study revealed that students expect their teachers to be competent not only in content delivery, but also as ©2016 The author and IJLTER.ORG. All rights reserved.

effective models of good classroom teaching. While students in other contexts are attracted to teachers who are well-dressed and exhibit likeable qualities, this research suggests that students are more readily drawn to professors who demonstrate professionalism and show interest in the well-being of their students. Understanding students’ expectations of their professors is important for establishing the type of professor-student relationship that inspires student success. In future research, it would be worthwhile to identify those professors who attract rather than repel students, in order to better understand the philosophy which informs their practice.

References Al-Mohaimeed, A. (2015). Medical faculty development: Perceptions about teachers’ characteristics. Journal of Taibah University Medical Sciences, 10(4). 405-410. DOI: 10.1016/j.jtumed.2015.09.002 Arnon, S. & Reichel, N. (2007). “Who is the ideal teacher? Am I? Similarities and differences in perception of students of education regarding the qualities of a good teacher and their own qualities as teachers.” Teachers and Teaching: theory and practice, 13(5), 441-464. http://dx.org/10.1080/13540600701561653 Crawford, P. L., & Bradshaw, H. L. (1968). Perception of characteristics of effective university teachers: A scaling analysis. Educational and Psychological Measurement, 28: 1079-85. Douna, P., Kyridis, A., Zagkos, C., Ziontaki, Z., & Pandis, P. (2015). The ideal university teacher according to the views of Greek students. International Journal of Higher Education, 4(20, 145-158. Epting, L. K., Zinn, T. E., Buskist, C., & Buskist, W. (2004). Students perspectives on the distinction between ideal and typical teachers. Teaching of Psychology, 31(3), 181183. Feldman, K. (1988). Effective college teaching from the students’ and faculty’s view: Matched or mismatched priorities? Research in Higher Education, 28(4), 291-344. http://dx.doi.org/10.1007/BFO1006402 Fortson, S. B., & Brown, W. E. (1998). Best and worst university instructors: The opinions of graduate students. College Student Journal, 32(4), 572-576. Giroux, H., A. (1988). Schooling and the struggle for public life: critical pedagogy in the modern age. Minneapolis: University of Minnesota press. Gao, M., & Liu, Q. (2013). Personality traits of effective teachers represented in the narratives of American and Chinese preservice teachers: A cross-cultural comparison. International Journal of Humanities and Social Science, 3(2), 84-95. Gurung, R. A. R. & Vespia, K. M. (2007). Looking good, teaching well? Linking liking, looks, and learning. Teaching of Psychology, 34, (1), 5-10. Hande, H., Kamath, S., & D’Souza, J. (2014). Students’ perception of effective teaching practices in a medical school. Education in Medicine Journal, 6(3), 63-66. Korte, L., Lavin, A., & Davies, T. (2013). An investigation into good teaching traits. Journal of Learning in Higher Education, 9(1), 141-150. ©2016 The author and IJLTER.ORG. All rights reserved.

Malik, A. N., & Bashir, S. (2015). Good teacher: Students perception about top qualities in health sciences. Professional Medical Journal, 22(5), 670-673. McLean, M. (2001), Qualities attributed to an ideal educator by medical students: Should faculty take cognizance? Medical Teacher, 23 (4), 367-370. http:// dx.doi.org/10.1080/01421590120057030 Obermiller, C., Ruppert, B., & Atwood, A. (2012). Instructor credibility across disciplines: Identifying students’ differentiated expectations of instructor behaviours. Business Communication Quarterly, 75(2), 153-165. DOI: 10.1177/1080569911434826 Roberts, D. C. (1981). Student leadership programs in higher education. Washington, DC: American College University Press. Singh, S., Pai, D., Sinha, N., Kaur, A., Soe, H., & Barua, A. (2013). Qualities of an effective teacher: What do medical teachers think? BMC Medical Education, 13(128), 1-7. Slate, J., La prairie, N., Schulte, D., Onwuegbuzie, A. J. (2011). Views of effective college faculty: A mixed analysis. Assessment & Evaluation in Higher Education, 36(3), 331346. Strage, A. (2008). Traditional and non-traditional college students’ descriptions of the “ideal” professor and the “ideal” course and perceived strengths and limitations. College Student Journal, 42(1), 225-231. Tam, K. Y., Heng, M., & Jiang, G. (2009). What undergraduate students in China say about their professors’ teaching. Teaching in Higher Education, 14(20, 147-159. Witcher, A. E., Onwuegbuzie, A. J., & Minor, L. (2001). Characteristics of effective teachers: Perceptions of preservice teachers. Research in the Schools, 8(2), 45-57.

International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 32-46, February 2016

The Effects of Goal Type, Learning Interest, and Task Difficulty on Learning English Words Pengcheng Zhang Nantong University Nantong, China Zhe Wang, Olusola Adesope Washington State University Pullman, United States

Abstract. Within the past few decades, goal-setting research has emerged as a prominent approach to motivation. However, little is known about the relationship among goal types, learning interest, and task difficulty. Using a 3 x 4 x 3 mixed experimental design, one hundred middle school students with different levels of learning interest (strong, moderate, and weak) in the present study were asked to learn English words of different levels of difficulty (high, medium, and low) under the context of different goal orientations (mastery-approach, mastery-avoidance, performance-approach, and performanceavoidance). Our results mainly showed that: (a) the main effects of learning interest, goal types, and task difficulty on performance were all significant; and (b) the interaction between goal type and task difficulty on performance was significant. Important educational implications are discussed as well as limitations and future directions. Keywords: Achievement goal; Interest; Task difficulty.

Introduction The topic of Goal-setting has become an underlying component of the research on academic motivation (van Dam, 2014). Goal-setting theory was formulated on the basis of Ryanâ&#x20AC;&#x2122;s (1970) belief that conscious goals influence action, which through four mechanisms. Specifically, goals are directive (Rothkopf & Billington, 1979), energizing (Bandura & Cervone, 1983); also, goals affect persistence (LaPorte & Nath, 1976) and lead to the active use of task-relevant knowledge, skills, and strategies (Wood & Locke, 1990). The primary interest of industrial-organizational

psychologists in predicting, explaining, and influencing performance has directed goal-setting researchers’ focus toward the relationship between performance goals and level of task performance (Locke & Latham, 2002). Goal-setting theory maintains that the goal itself has an incentive effect, which can turn people’s needs into motivation, make people's behavior accord with a planned direction, and contrast the results of their own behavior to the established goal to assess the discrepancy and fill the gap between them timely so that the goals can be achieved ultimately (Cao & Liu, 2011). Since the mid-1980s, many attempts have been made to distinguish between mastery goals (aiming to develop and gain one’s competence) and performance goals (aiming to demonstrate one’s competence relative to others) (e.g., Ames & Archer, 1988; Nicholls, 1984; Preenen, van Vianen, & De Pater, 2014). Later, researchers began to realize that approach-avoidance was also a primary distinction that deserved a core position in the conceptualization and classification of goal types (Elliot, 1999; Pintrich, 2000a). According to these researchers, approach goals were directed toward positive or desirable events, whereas avoidance goals were aimed at avoiding negative or undesirable events. Therefore, adding the goal valence dimension to the theory allows both mastery and performance goals to be framed in either an approach manner or an avoidant manner (Senko & Hulleman, 2013), leading to four specific goal types, which are mastery-approach, performance-approach, mastery-avoidance, and performance-avoidance goals. The mastery-approach goal is a goal orientation improving individuals’ own ability as a pursuit of learning through cultivating the sensitivity of individual perception and the autonomy of behavior and emphasizing on the close relationship between learning and growth (see Dysvik & Kuvaas, 2010). The mastery-avoidance goal is a goal orientation that individuals actively adopt various measures trying to evade any performances of their own imbecility as a pursuit of learning (Madjar, Kaplan, & Weinstock, 2011). The performance-approach goal is a goal orientation that individuals try best to demonstrate their ability and expect to get a positive evaluation on the ability from others as a pursuit of learning (Roussel, Elliot, & Feltman, 2011). The performanceavoidance goal is a goal orientation that individuals try to evade the comparison with others which displays their imbecility or negative evaluations by others on their own ability as a pursuit of learning (Smillie, 2008; Law, Elliot, & Murayama, 2012). Building on the 2 × 2 goal framework, much research has emerged examining the role of each goal type in learning performance (e.g., Cury et al, 2006; Elliot & Murayama, 2008; Murayama et al., 2011).

An important theoretical framework underlying research on goal setting is that students are motivated by their personal dispositions as well as the environments (Ames, 1992b; Maehr, 1984; & Nicholls, 1989). Also, Tuominen-Soini, Salmela-Aro, and Niemivirta (2011) suggested that in a given situation, students tend to adopt goals depending on both dispositional tendencies and external settings. In other words, the studentâ&#x20AC;&#x2122;s goal orientation does not remain unchanged and may vary depending on different settings in which they find themselves. Patrick, Kaplan, and Ryan (2011) conducted a study showing that perceived classroom mastery goal structure correlates substantially with perceptions of the teacher as promoting classroom mutual respect and providing emotional and academic support and relates closely to perceiving the teacher as promoting student learning-related discussion. TuominenSoini, Salmela-Aro, and Niemivirta (2011) offered evidence for change in achievement goal orientations over time although the changes were small. The Relationship among Learning Interest, Goal Types, and Task Difficulty It has been acknowledged that mastery goals are closely aligned with intrinsic motivation and thus are deemed directly relevant to a framework articulating motivation and engagement (Brophy, 2005). Although most studies positioned mastery goals as a more effective motivational orientation, the debate as to mastery-oriented goals versus performance-oriented goals has never ceased. For instance, Martin (2007) found that mastery goals are more positively associated with educational aspirations, class participation, and enjoying school than are performance goals, whereas Kaplan & Middleton (2002) pointed out that performanceapproach goals may contribute to positive outcomes in competitive learning environments; or may be connected with certain types of positive outcomes such as achievement. Besides, Harackiewicz et al. (2002) identified positive potential of performance-approach goals and ways performance-approach goals can be integrated with mastery goals to enhance optimal motivation. In response to the debate and research findings that have been diffuse, we reasonably argue that the advantage of specific goal orientations may depend on certain individual characteristics and/or contextual factors such as task difficulty. Goal setting has become one of the most important motivational factors believed to influence achievement (Elliot, 2005; Anderman et al, 2006; Kaplan & Maehr, 2007). At the same time, a robust body of studies (Ryan & La Guardia, 1999; Renninger, 2000; Hidi, 2006) in the field of interest

showed that situational and/or individual interest had an enormous impact on learning outcomes. Harackiewicz, Barron, Tauer, and Elliot (2002) provided empirical evidence that the students' learning interest was positively associated with their final achievements. Goal setting and interest, conceptualized as two affective factors, however, have not received adequate attention in terms of potential interactions between them. Among the few is the study conducted by Harackiewicz, Durik, Barron, Linnenbrink-Garcia, and Tauer (2008) suggesting that initial interest motivates individuals to adopt mastery goal approach and then this approach can facilitate the development of interest. In addition, although Senko and Harackiewicz (2005) focused on the effects of achievement goals and interest, they only investigated the masteryapproach and performance-approach goals. Besides individual characteristics, many studies argued that learning activity relevant features such as task difficulty plays a critical role in performance (e.g., Chae, Seo, & Lee, 2015; Marshall & Brown, 2004). There are few studies conducted on the relations between goals and task difficulty. Among the exceptions, Kuman and Jagacinski (2011) found that increasing levels of difficulty lead to declining levels of performanceapproach goals and increasing levels of work-avoidance goals. Li, Lee, and Solmon (2007) examined task difficulty in relation to self-perceptions of ability, intrinsic value, attainment value, and performance and found that initial self-perceptions of ability negatively predicted perceptions of task difficulty. However, research on the moderation effect of task difficulty on the goal-outcome relationship has received less than adequate attention, making the need for taking task difficulty and goal type as two factors predicting learning outcomes pressing. In summary, given the dearth of studies on investigating learning outcomes from an integrated perspective, research is needed to clarify the complex relationship among goal type, learning interest, and task difficulty. Overall, we raised two hypotheses: (1) Significant main effects of learning interest, goal type, and task difficulty are expected; and (2) a significant interaction among learning interest, goal type and/or task difficulty on the achievement is expected. Given that goal orientations can be changed depending on different environments according to the literature we just reviewed, the present study set four learning scenarios determined by different instructions under which participants were hypothesized to develop a certain type of goal orientation.

Method Participants and Design Two hundred and forty students (124 girls and 116 boys) from 20 classes of 11 middle schools in China participated in the formal study. Participants’ mean age was 14.5 years (SD = 0.82). All participants were Chinese and most of them had learned English as the second language for 3 years. A 3 (learning interest) by 4 (goal type) by 3 (task difficulty) mixed experimental design was used, in which both learning interest and goal type were between-subjects variables whereas task difficulty was a within-subjects variable. Participants in each interest condition were randomly assigned to one of the four goal-type conditions. Materials Learning material was a sheet where English words were presented. All the words were classified into three categories according to three difficulty levels (high, medium, and low), with each category consisting of 40 words. The difficulty level was determined by the length of words. Specifically, words composed of eight letters were considered as highdifficulty (e.g., abidance); words of six letters (e.g., castle) were considered as medium-difficulty; and words of four letters (e.g., lava) were considered as low-difficulty. Measures Students’ mid-term scores were used as a pretest measure. A one-way analysis of variance (ANOVA) showed no significant differences among the conditions. Students’ interest in learning English was assessed by a 7-point Likertscale including one item (How much are you interested in learning English?) ranging from 1 (not interested at all) to 7 (very much interested). Responses ranging from 1 to 2 indicated weak learning interest; 3 to 5 indicated medium learning interest; and 6 to 7 indicated strong learning interest. Students’ learning performance was assessed by a recognition test. The ratio of the number of words in the recognition test to the number of words in the learning phase is 2.5:1. The similarity between old and new words was controlled in two ways (the same length and the same structure). There were 40 words presented on the reading material and 100 words presented on the recognition test. Each student was given one point by correctly recognizing a word, yielding a possible score ranging from 0 to 100.

Procedure Before the formal experiment was carried out, we recruited 800 students randomly from 11 middle schools in Shanghai to complete a survey regarding learning interest about six main subjects including politics, geography, Chinese, English, mathematics, and history. The participants rated on a 7-point Likert-scale ranging from 1 (not interested at all) to 7 (very much interested). Responses of 1-2 indicated weak learning interest; 3-5 indicated medium learning interest; and 6-7 indicated strong learning interest. Eight hundred questionnaires were distributed and 767 questionnaires were collected. According to the results of the survey, students’ interest in learning English was comparatively evenly distributed on three levels, which were strong, medium, and weak. Therefore, English words as learning material were selected in the present study. Next, 80 students were randomly selected by the experimenter out of those with strong interest in English; 80 students were randomly selected out of those with medium interest in English; and 80 students were randomly selected out of those with weak interest in English, yielding a total of 240 final participants in the present study. Different types of goals were designed based on different instructions given. The instruction used to set up the mastery–approach goal was: We welcome you and appreciate your willingness to take part in this study. There are 40 words in the sheet. Please learn as many words as possible when you read them. At the end, the more words you can remember the more rewards you will get. The instruction used to set up the mastery–avoidance goal was: We welcome you and appreciate your willingness to take part in this study. There are 40 words in the sheet. Please learn as many words as possible when you read them. In the end, you can leave early if you remember more; otherwise you will have to stay and clean the classroom together with the experimenters. The instruction used to set up the performance-approach goal was: We welcome you and appreciate your willingness to take part in this study. There are 40 words in the sheet. Please learn as many words as possible when you read them. In the end, the higher your ranking is, the more rewards you will get. The instruction used to set up the performance-avoidance goal was: We welcome you and appreciate your willingness to take part in this study. There are 40 words in the sheet. Please remember as many words as possible when you read them. In the end, if you rank higher, you can leave early; if you rank lower, you will have to stay and clean the classroom together with the experimenters.

In each goal condition aforementioned, the students were then required to read and memorize the English words in 30 minutes. After the 30 minutes had passed, the students were required to work on the recognition test. After the answer sheet had been collected, the participants were thanked, debriefed and dismissed. Results Main Effects Before we analyzed the data, all variables were examined for assumptions of parametric data. No univariate or multivariate outliers were identified (Tabachnick & Fidell, 2012). Given that the assumption of sphericity was violated based upon the Mauchlyâ&#x20AC;&#x2122;s test resulting in the variations across different conditions (high difficulty, medium difficulty, and low difficulty) that are not similar, the Greenhouse-Geisser correction was employed to produce a valid F-ratio (Field, 2013). Table 1: Descriptive statistics of achievements for different levels of task difficulty, goal types, and learning interest.

Masteryapproach goal stron gener wea Interest g al k task M 78.0 77.5 73.5 difficulty SD 10.7 11.1 13.1 (high) MSE 2.39 2.48 2.93 task M 85.2 81.9 78.6 difficulty SD 10.1 9.2 14.8 (medium) MSE 2.26 2.06 3.31 Task M 87.9 82.4 80.9 difficulty SD 9.1 8.5 12.9 (low) MSE 2.04 1.90 2.89

Masteryavoidance goal stron gener wea g al k 70.9 60.35 49.9 10.8 13.0 15.2 2.42 2.91 3.40 77.6 65.4 59.1 13.9 16.9 15.0 3.11 3.78 3.36 91.7 88.9 86.9 5.8 7.3 9.0 1.30 1.63 2.01

Performanceapproach goal stron gener wea g al k 78.0 68.5 59.2 13.8 14.8 13.5 3.09 3.31 3.02 85.9 84.2 75.9 11.2 12.0 14.4 2.51 2.68 3.22 85.6 79.2 78.2 9.4 9.8 11.4 2.10 2.19 2.55

Performanceavoidance goal stron gener weak g al 73.8 63.8 60.2 14.2 13.4 11.5 3.18 3.00 2.57 75.9 73.5 70.3 11.8 13.6 14.8 2.64 3.04 3.31 93.1 89.1 82.9 5.7 8.1 10.6 1.28 1.81 2.37

Achievement test score means and standard deviations were reported in Table 1 for between-subjects and within-subjects variables. The result demonstrated that the main effect of the learning interest was significant, F (2, 228) = 54.21, MSE = 135.97, p < .01; partial eta squared = .32. When learning interest was strong, moderate, and weak, the mean achievement scores were M = 81.66; M = 76.17; and M = 70.58 respectively. In addition, the main effect of goal types was significant, F (3,228) = 12.18, MSE = 135.97, p < .05; partial eta squared = .138. It is apparent that the descending order of achievement for each different goal type was: mastery-approach goal, performance-approach goal, performanceavoidance goal, and mastery-avoidance goal (Table 2). At the same time, the main effect of task difficulty was also significant, F (2, 228) = 110.30,

MSE = 149.75, p < .01; partial eta squared = .33. Table 2: Descriptive statistics of achievements for different goal types

MasteryApproach

Performanceapproach

Performanceavoidance

Masteryavoidance

80.65

77.18

75.84

72.3

11.06

12.26

11.52

11.88

Interactions The results of univariate tests showed that generally, there was no significant interaction among learning interest, goal type, and task difficulty on achievement, F (12, 228) = 1.04, p = .413, partial eta squared = .027. In addition, the interaction effect between learning interest and goal types in between-subjects was not significant, F (6, 228) = 1.94, p = .075, partial eta squared = .049. The interaction effect was also not significant between learning interest and task difficulty, F (5, 228) = 1.27, p = .24, partial eta squared = .011. However, a significant interaction effect (see Figure 1) was detected between goal type and task difficulty, F (6, 228) = 18.70, p < .001, partial eta squared = .198. We specifically focused on the goal type – task difficulty relation given its significant interaction. The analysis of simple effect revealed that, with high difficulty, the descending order of achievement for each different goal type was: mastery-approach goal, performance-approach goal, performance-avoidance goal, and mastery-avoidance goal. Using Tukey’s honestly significantly difference (HSD) post-hoc test with alpha less than .05, it was found that there was no significant difference between the performance-approach goal and the performance-avoidance goal (p > .05). For the remaining contrasts, significant differences were detected. The analysis of simple effect with moderate difficulty portrayed the descending order for each different goal type as: performance-approach goal, mastery-approach goal, performance-avoidance goal, and masteryavoidance goal. The HSD test showed that there was no difference between the performance-approach goal and the mastery-approach goal or between the performance-avoidance goal and the mastery-avoidance goal (both ps > .05), whereas there were significant differences for the remaining contrasts. With low difficulty, the descending order for each different goal type was: mastery-avoidance goal, performance-avoidance goal, mastery-approach goal, and performance-approach goal. The HSD test showed that there was no significant difference between the mastery-

avoidance goal and the performance-avoidance goal or between the mastery-approach goal and the performance-approach goal (both ps > .05) while significant differences for the remaining contrasts.

Goal types Mastery–approach goal Mastery–avoidance goal Performance-approach goal Performance-avoidance goal

90.00

Achievements

现

85.00

80.00

75.00

70.00

65.00

60.00

high

moderate

low

Task difficulty Figure 1: Interaction between goal types and task.

Discussion One important aim of the present study was to examine the main effect of learning interest. As hypothesized, this study demonstrated that the main effect of the learning interest was statistically significant. That is, the interest effect is independent of other factors (e.g., goals and task difficulty in this study), which can be interpreted as: the stronger the learning interest is, the better the performance is expected. The result is consistent with findings from previous research (Hidi, 2000; Van Yperen, 2003; Harackiewicz & Hulleman, 2010). From the perspective of emotional psychologists (Smith, Sansone, & White, 2007; Renninger, 2009), serving cognitively and emotionally, interest is considered to be underlying intrinsically motivated behavior and central to the amplification and direction of attention and thus increases cognitive engagement and promotes understanding. As expected, we found that when the level of task difficulty was high, the individuals setting mastery-approach goal outperformed those who had other goal orientations. It is possible that the mastery-approach goal is closely related to individuals’ self-improvement and growth. In order to develop their competence and/or task mastery, individuals tend to consider the task of high difficulty as an opportunity to improve, which enables them to concentrate on the task and engage in learning activities

accomplishing it actively and passionately, and thus facilitates their learning. This finding can be interpreted by the desirable-difficulties hypothesis - namely, that creating difficulties for the leaners during meaningful acquisition can actually promotes retention and transfer (Bjork, 1994; Yue, Bjork, & Bjork, 2013). Given that mastery-approach goals contribute to arousing intrinsic motivation, this finding partly aligns with the study conducted by Anshel and Weinberg (1992), who found that difficult goals increased intrinsic motivation, whereas easy goals decreased intrinsic motivation. Also, the finding is in accordance with the study by Izadikhah, Jackson, and Loxton (2010). For individuals who set performance-approach goals, they performed the second best among the four goal types. It may suggest that when faced with difficult tasks, individuals view outperforming their peers on difficult tasks as a way to gain confidence and recognize their own ability, which would stimulate their motivation and enhance learning outcomes. However, the individuals who set the mastery-avoidance goal were outperformed by those driven by all the other three goal orientations. One possible explanation is that although mastery goal prompted the individual to strive hard, meanwhile the inclination of avoidance when dealing with the tasks of high difficulty might cause the individual to struggle and thereby incur the approach-avoidance conflict, which could lead to learning anxiety and distraction and thus overload the individual’s working memory resulting in poor performance (Elliot & McGregor, 2001; Van Yperen, Elliot, & Anseel, 2009). For the low-difficulty task, however, we found that those setting the mastery-avoidance or performance-avoidance goal outperformed those who set the mastery-approach or performance-approach goal. In other words, regardless of that the individual prefers to gain their own mastery or compares their competence with others’, the avoidance of undesired consequences serves as a primary drive of effortful involvement in learning activities when the difficulty level of the task is low. Although the finding is in contrast to some other research revealing avoidance goals have a hindering effect on learning (Bartels & Magun-Jackson, 2009; Brodish, & Devine, 2009; Luo et al, 2011; Bong, Hwang, Noh, & Kim, 2014), it may be the case that given the task is of low difficult, the tendency of avoidance will not lead to the overloading effect from the approach-avoidance conflict. As per mastery-approach goals, individuals don’t hold the belief that completing an easy task is beneficial enough to assist them in gaining competence or mastery. Hence, when they are in a learning environment shaped by mastery-approach goals, their attention may be distracted, which can harm performance. Likewise, they tend to

think that their completion of an easy task is not a convincing indicator of their better competence relative to others because they believe that most people would be able to reach the same desired level of performance easily. In conclusion, the results of the present study provide two crucial educational implications that educators may consider. First, the finding that increased learning interest leads to better performance when the goal type and task difficulty remain constant suggests that teachers and parents should make effort to arouse students’ learning interest at any time. In addition, since the interaction between goal types and task difficulty was significant, teachers and parents should pay attention to assessing different goal types to set an appropriate one depending on the difficulty level of a specific task. Limitations and Future Research Directions A major limitation of the present study is our exclusive focus on junior middle school students in the context of remembering English words. In order to improve the generalizability and fully understand the interactional relationship among goal types, interest, and task difficulty, future studies may examine the 3 × 4 ×3 model with college students and with students in other subject matters such as mathematics. Another drawback is that it might not make sense to distinguish different levels of difficulty merely by classifying words based on the number of letters each word consists of. It is possible that words are to be learned consisting of more letters would turn out to be easier ones as compared words of less letters because certain patterns and roots could be recognized in long words, rendering memorizing them more efficient. Future research is needed to evaluate the difficulty level from the angle of learners (i.e., self-reported difficulty). We analyzed task difficulty as the within-subjects variable due to the limited number of students. A limitation associated with asking the same student to work across different tasks and take different tests is that there might be threats to internal validity. For example, although the learning materials varied in content (words of 4 letters, words of 6 letters, and words of 8 letters), they were presented in the same form (words after words), resulting in practice and/or familiarity the students gained after each test that could be mistaken for treatment effects. Therefore, future studies recruiting more participants and operationalizing task difficulty as a between-subjects variable may reduce potential threats to internal

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International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 47-64, February 2016

An ICT Approach for Implementing Emerging Technologies for Teaching and Learning in Low Resource Communities: Lessons Learnt from Namibia Shehu M and Jere N.R Namibia University of Science and Technology Windhoek, Namibia

Abstract. In this paper, emerging technologies in education which include an interactive mobile learning application and new electronic reading devices for Namibian Schools are discussed. The paper explains how each of the studies was conducted and lays out the findings from each of the studies. Our major aim is to design an ICT approach that could be used in Namibia to implement emerging technologies within the Namibian education system. A case study qualitative approach was used. This was supported by data collection methods such as interviews and focus groups, as well as by data analysis paradigms comprising of a mix of Constructivist and Classic Grounded Theory. Results from the studies showed negative results which may hamper implementation of the new technologies in Namibian schools. For example, on the issue implementing e-readers in Namibian schools, the Namibian education stakeholders were supportive of the idea but sceptical of its current viability. They appreciated the potential benefits that the e-readers could provide, but mentioned that a lot has to be done first in terms of establishing the supporting ICT infrastructure. We concluded that there was lack of a guiding approach that could be followed in implementing emerging technologies in low resource areas. This workshop paper provides the findings from the engaged participants and lessons learnt from the studies. The focus of this paper is to outline the views of education stakeholders in Namibia on the implementation of new ICTs. Keywords: emerging technologies, ICTs, teaching and learning

Introduction The international community emphasizes the role of education in bringing about sustainable socio-economic development. For instance, Goal 2 of the United ÂŠ 2016 The authors and IJLTER.ORG. All rights reserved.

Nations Millennium Development Goals aims to achieve universal primary education for children everywhere, boys and girls alike, by 2015 (Valk, Rashid & Elder, 2010). Specific to Namibia, the imbalances and inequalities between rural and urban schools means that the same educational achievements are difficult to attain across the country. In addition to this, most urban schools possess ICTs and have incorporated e/m-learning at school. As a result, despite the continuous technology developments witnessed in many urban areas, Namibian rural schools remain mostly unreached. On the other hand, developing countries face several challenges when attempting to successfully implement ICT solutions in education sectors. These challenges include, but are not limited to, technological illiteracy and a fear of change among various stakeholders (Keller, 2010; Hovious, 2014). These problems are further exacerbated by the presence of a low reading culture among their school learners (Barker, 2011), as well as the lack of a proper engagement and needs-assessment process when implementing ICT solutions. From a global perspective, technology is changing at a rapid pace and new ICT solutions are required in all sectors of a developing economy, most especially its education sector. In addition to these problems, there is no standard implementation plan that is currently in place which ICT stakeholders could follow when introducing new technology. This paper explains a study which was conducted in Namibia, which proposed e-readers as a new reading solution in Namibian classrooms. The paper outlines an overview of the study, how it was done and its major findings. The main focus is to expose the current Namibian environment and how that affects implementation of emerging technologies. The paper shows the current state of the views of learners, teachers and education stakeholders in implementing emerging technologies. The next step is to propose best approaches, techniques and supporting theories that could be useful in the application of modern technologies to Namibiaâ&#x20AC;&#x2122;s education system.

Overview of Namibian schools Namibia has 1400 schools operated and administered by the state and 100 schools operated by the private sector (Fischer, 2001). The Namibian constitution and the Education Act (2001) define the frameworks for the educational system: compulsory seven (7) years of primary school for children aged 6-12 and five (5) years of secondary education for children aged 12-18. Schools are well spread across the country both in rural and urban areas with the majority residing in rural areas. Schools in rural areas have historically poor performance metrics on the national standard examinations compared to the urban-area schools; this is caused by several imbalances within the system. Leaners attending schools in urban areas are exposed to excellent learning resources and state-of-the-art infrastructure such as computers, internet access, libraries, transportation etc. and this gives them a definite learning advantage over learners in rural-area schools, which is reflected by good grades in the national standard exams (Fischer, 2001).

The Namibian education system is structured as follows: Table 1: Namibia's education system structure INSTITUTION STARTIN CYCLE LEVEL S G AGE Universities, Polytechnics, Tertiary Tertiary Vocational Centers Second Senior High Secondary 15 Cycle School schools Education Basic Education Junior High 12 (Free Education) School First Cycle Primary School 6 Education Kindergarten

YEAR S

4 yrs 2 yrs 6yrs 2yrs

An understanding of the Namibian education system is vital as this formed part of the sample size and provided guidance in deciding on which schools to engage. Appropriate use of ICT can catalyse the paradigmatic shift from teachercentred pedagogy to more effective learner-centred pedagogy (Hare, 2007). For this paper only the second-cycle education schools were considered. We also observed a couple of challenges within the Namibian schools that were almost similar to the observations of Power & Sankale (2009) who mention that the education system faces challenges in implementing ICTs in teaching and learning such as; ● Teachers and learners being computer illiterate ● Lack of ICT facilities ● Lack of electricity Research objectives: The objective of this paper was to propose an ICT approach that could be used in introducing new technology in Namibia. This could be achieved by determining the key actors and factors that will play a role in the successful implementation of e-readers in Namibian educational institutions.

Technology in education Namibia has shown progress when it comes to mobile application development even though not necessarily in learning (Stork & Calandro, 2011). The directorate of examinations together with local mobile operators introduced a system whereby grade 10 and 12 students get their examination results via text messages. This system works on any type of phone; one only needs to send a SMS to a provided SMS line. In similar projects, SchoolNet Namibia offers local hands-on ICT deployment, training and support (Ballantyne, 2004). It is an organization that was established in February 2000 to empower youth through the internet and provide sustainable, low-cost internet-based solutions to all Namibian schools. © 2016 The authors and IJLTER.ORG. All rights reserved.

In cases where ICTs have been introduced in the education sector, there are still common challenges experienced such as underutilization of ICTs and poor ICT implementation strategies. Implementing e-readers in Namibian schools was proposed. The benefits of e-readers include portability, low energy consumption, increased capacity for educational content storage at no extra weight, low price and Wi-Fi connectivity. E-Readers can be utilized in Namibiaâ&#x20AC;&#x2122;s education sector to solve some current problems, especially the lack of teaching & learning materials. This study, therefore, aimed to assess the readiness of the Namibian academic community at large to the deployment of e-readers in schools and tertiary institutions, as well as to outline appropriate implementation strategies for successful e-reader integration into Namibian schools. Main theories considered Learning is the result of experience having a permanent change on our behavior (Huitt, 2013). With educators regularly considering the use of use new curricula, teaching methods and assessments, separating the wheat from the chaff when it comes to the assessment of these methods necessitates a grounded understanding of the foundational theories that teaching is based upon, such as how students learn and what they should learn (Wilson & Peterson, 2006). There are several schools of thought related to this issue, each espousing its own assumptions, principles and methods. An overview of these theories is presented next (Huitt, 2013). Table 2: Schools of thought regarding learning theories

Assumptions

Primary Focus

behavior al

Stimuli and response s to them

Environ mental forces dictate learning

informat ion processi ng Acquirin g knowled ge and critical thinking skills Mental operation s dictate learning

social learning, cognitive social humanisti constructivi constructiv c sm ism & social cognition Needs Mental and Attitudes and selfdevelopme and social esteem ntal influences processes towards attaining goals Emotional influences dictate learning

Individual constructio n dictates learning

connectiv ism

Developm ent through interactin g with digital networks Social Digital environmen social ts dictate networks learning dictate learning

Principles

Biologica l bases of behavior Actions and conseque nces

Changes over time in complexi ty Standard s

Individual ity Selfdetermina tion Setting dreams and goals Clinical method Pencil and paper

Diagnose learner readiness Help students learn on their own

Peer and adult interaction Individual responsibili ty

Digital networks influence learning Personal constructi on of meaning Mostly qualitativ e

Methods

Experime Experime Natural and Experiment ntal ntal/ structured al, methods correlatio observation systematic Systemati nal observation c lab Pencil Paper and observati and pencil on paper The Connectivism school of thought is of particular relevance to this study, as it emphasizes contemporary learning through connection to digital networks. The introduction of e-readers avails (and requires) connectivity to the internet for group work and study, content lookup, assignment grading and self-study. Furthermore, one of the principles of Connectivism is that personal construction of meaning is critical, which plays an important role in how students should ideally study and absorb content in the classroom. It consequentially emphasizes the production of knowledge rather than just the consumption of it, and the aggregation of several such personally produced content to a knowledge base for the benefit of other present and future learners to use. A vivisection of Table 2, focusing on the principles of each theory from the first-person perspective, looks as follows:

Table 3: Theories of learning and their principles, adapted from Huitt (2013) Theory Principles ● Define goals and break them down into sub-objectives ● Interact with the material (take notes) Behavioral ● Rewards for accomplishing objectives ● Pay attention in class and during study. ● Identify major terms and concepts before studying. Information Processing ● Try to apply concepts you learn ● Relate your learning to your life ● Be comfortable while learning; avoid stress Humanistic ● Make the study and learning process fun ● Relate new material to concepts you’ve already Cognitive encountered before Constructivism ● Try to work, learn and study with another student ● Group study Social Learning, Social ● Set concept-learning goals Constructivism & ● Develop the best methods of learning and studying, and Social Cognition learn from others ● Connect with knowledge bases and other inquirers. Connectivism ● Produce knowledge, do not just consume it © 2016 The authors and IJLTER.ORG. All rights reserved.

The theories assisted in understanding how ICTs could be integrated into the teaching and learning process in Namibian schools. We note, however, that the introduction of technology into the classroom requires certain considerations to be made. Wilson, Zygouris-Coe & Cardullo (2014) introduce to us the concepts of “deep learning” and “deep trouble”, defining deep learning “as using knowledge and skills in ways that prepare students for real life and deep trouble as “what happens in classrooms that adopt technologies without a plan, purpose, teacher professional development, and a school culture that neither embraces nor supports teaching and learning with technology” (Wilson et al., 2014). Study approach Being a body of research primarily concerned with the introduction of new technological tools into the education sphere, it was most appropriate that it be conducted under the umbrella of design-based research. Furthermore, due to its relatively novel status within the Namibian education sphere, it was likewise apt that any and all data collected should be analysed through a combination of Classic and Constructivist Grounded Theory. Both the Design-Based Research (DBR) approach and the underpinning analytic foundation of Grounded Theory were applied in this study. A non-exhaustive description of DBR follows in the next section. Defining Design-Based Research (DBR) Design-Based Research focuses on solving broad-based, complex, real world problems that are critical to education, with the end-goal of making contributions both scientific and applied to the field (Reeves, Herrington, & Oliver, 2004; van den Akker, 1999; Herrington, McKenney, Reeves, & Oliver, 2007). They however concur that DBR protocols require intensive and long-term collaboration involving researchers and practitioners, and that it meshes practical solutions to sector-based challenges with the acknowledgement of reusable design principles. Van der Akker (1999) further points out that in DBR output is measured as design principles, aiming to benefit to all stakeholders involved (Reeves, 2000). Persistent, significant problems exist in education research and this cyclic nature necessitates practitioners to become more directly involved in the research by collaborating with relevant stakeholders within the sector (Cotton, Lockyer, & Brickell, 2009; Reeves & Hedberg, 2003). DBR thus applies to this research in the sense that after the initial feedback solicitation (which is the scope limit of this thesis), further research will need to be undertaken to ensure thorough data collection, especially from other schools both at the secondary and tertiary levels within Namibia. Piloting of proposed ICT interventions would then follow, and this would in turn necessitate the monitoring and evaluation of the interventions thereafter. Phases of Design-Based Research In formulating our own ICT integration strategy for e-readers in Namibian schools, we loosely modelled it upon the guidelines of design-based research.

The guidelines of this underpinning theory are explained in the following sections. Phase 1: Problem Definition In this phase, researchers and educators collaborate to identify and define practical problems within education. This involves problem and objective definition in addition to fleshing out the research questions and performing a review of relevant literature (Bannan-Ritland, 2003; Herrington, McKenney, Reeves, & Oliver, 2007; Gay, 1992; van den Akker J., 1999). Phase 2: Theoretical Framework Definition This phase requires defining the theoretical framework and draft principles that will underpin all the research to be undertaken. DBR is best suited to pragmatic theoretical foundations, wherein the theoryâ&#x20AC;&#x2122;s value is in its capacity to produce tangible change. The proposed intervention of change is also defined in this phase (Barab & Squire, 2004; Cobb, Confrey, diSessa, Lehrer, & Schauble, 2003; Herrington, McKenney, Reeves, & Oliver, 2007). Phase 3: Iterative testing This phase involves the selection of methodologies (either quantitative or qualitative), the participants (whose selection must be contextually relevant to the study) and iterations of intervention implementation in order to fine-tune and further perfect the preferred solution to the defined problem. Data analysis is also carried out at this stage (van den Akker, Gravemeijer, McKenney, & Nieveen, 2006; Herrington, McKenney, Reeves, & Oliver, 2007). Phase 4: Production of design principles This final phase sees the distillation of the data received and analyzed into key design principles that can be used to guide future implementations of interventions, to inform policymaking as well as to expose all parties involved to new methods of teaching and learning (Herrington et al., 2007).

Description of proposed intervention In order to elicit sufficient data on key variables pertinent to this study such as the viability, usability and desirability of implementing e-readers into Namibian schools, it was important to engage the relevant end-users, namely schoolteachers and students. For the purposes of this study, the consideration of other variables such as affordability was impractical at this stage, as the proposed intervention was not yet at the pilot stage. This research was based on questionnaires handed out to students and teachers in three (3) different schools within the Khomas region in Namibia across a broad range of subjects and ages, as well as interviews with administrators at schools where e-reader programmes have already been implemented. Finally, intensive interviews with upper management staff at one of the leading Namibian Publishing Houses rounds out our studyâ&#x20AC;&#x2122;s data collection. The following section explains the approach used to identify the sample selection, interviews and data analysis.

Sample Selection For the purposes of this study, three schools were selected within the urban areas, two of which are government schools and one of which is a private school. The reason for this was to provide a balanced point of view with regards to ownership and usage experience of e-readers and similar devices in general, as private school children are significantly likelier to have owned and used an iPad before, thus skewing the data. Questionnaires A total of one hundred and fifty (150) questionnaires were handed out to students in these three schools via their teachers, with whom a previous faculty affiliation existed. All the questionnaires were returned within two weeks of the hand-out date. The teachers handed out the questionnaires to their students during class times, and themselves filled in their own specially made version of the questionnaire (“Teacher’s Questionnaire”). The grades of the students range from Grade 8 to Grade 10, with ages falling between 11 and 17+. We present descriptive statistics on these demographics, as well as their answers to the most pertinent questions. Interviews Three separate interviews were conducted with three different key actors in the education arena. All interviews were recorded using a voice recorder. The first interview was with the pioneer of an iPad study tool program at one of the leading schools in Windhoek. The second was with the head librarian at the same school who introduced an online e-book platform to the school to allow students to read books without having to physically go to the library. The third interview was with a senior staff member at one of Namibia’s leading publishing companies, NPH (“Namibian Publishing House”). All interviews contained broad ranges of questions designed to elicit, inter alia, the number of years they have currently worked in their respective fields, their thoughts on the reading culture in Namibia, the challenges they have faced in their respective initiatives and their thoughts on the future of e-reading and e-readers in Namibian classrooms. Data analysis The questionnaire data was entered and sorted using Microsoft Excel spreadsheet software, while the interview recordings were transcribed with the help of Microsoft Windows Media Player software. The quantitative data was analyzed using simple statistical analysis. Percentages were derived from the number of students (or teachers) who took a certain point of view as a part of the total. Agreements and emphatic agreements (“Agree” and “Strongly Agree”) were counted as a combined metric; therefore, if 50% of the students agreed on a view, and a separate 25% of the students strongly agreed on the same view, then the view was calculated as having a combined total of 75% of the respondents in agreement of that view. The same process applied for disagreements and emphatic disagreements. In terms of analyzing the interview data, thematic summaries were first noted down and categorized accordingly so that main ideas and themes could emerge. These summaries allowed us to notice broad differences and similarities in © 2016 The authors and IJLTER.ORG. All rights reserved.

challenges being faced in the respective fields. Further review of the literature combined with iterative analysis of the collected data consisted the process of developing codes, the next step in the Grounded Theory data analysis paradigm. Exploring emerging concepts and themes in the data and searching for potentially disconfirming evidence that could have gone against the findings were further steps that we took during data analysis (Kraft, et al., 2014). Data analysis in this research was carried out using Grounded Theory. This method allows themes, issues and important topics to emerge from the data through iterative analysis of said data; these topics then form the basis for subsequent analysis (Glaser & Strauss, 1967). Study findings Following below are the major findings that were culled from the second study. The results are divided into two sections, based on whether the results were students or teachers. STUDENTS Ownership of e-readers and internet access In terms of online access and e-reader ownership, just over half of the sampled students (53%) have internet access at home, while 43% do not have internet access at home. On the other hand, a significant and unsurprising 82% of students do not have e-readers, and only 15% of the students have e-readers. This overall low level of connectivity can be attributed to low incomes and limited knowledge of the existence of e-readers themselves, as most of the students were sourced from government schools which generally consist of learners from low income backgrounds. However, 83% of the respondents categorically stated that they would like to have internet access to help them with their school work. Books over laptops When asked whether they would prefer reading on a PC/laptop than from a book, a combined total of 43% disagreed, compared to only 38% agreeing that it would be better to read from a PC/laptop than a book. This percentage could be explained by the already low rates of e-reader ownership among learners. A further 15% of the respondents remained neutral on the topic. A significant 66% of respondents further stated that they prefer having pictures rather than text material, with 42% preferring material to be in color rather than plain black and white. More interesting content leads to improved focus A significant 65% of the students did not find school work boring, but around the same number (64%) went on to state that they would focus more on their school work if it was more interesting. As an indicator, a healthy 76% stated that they would also like to watch educational videos in addition to their text materials.

Electronic devices mean better studying Firstly, most (66%) of the students expressed the opinion that they carry too many school books every day. In addition to that, a whopping 60% of the students categorically stated that they would study better if they used electronic devices such as iPads to study, compared to only 25% disagreeing with the proposition. They also mostly preferred the convenience of online assistance with studying, as 72% of the students sometimes wished they could immediately look up difficult terms, phrases or concepts online while reading their school books.

Figure 6: Assertions among study participants Digital books over physical ones Conclusively, the majority of the students (63%) would prefer digital books over physical books. Teachers From a sample of 11 teachers, 6 of them had taught for more than 11 years each. The majority (63%) had never owned a tablet phone/device before, but all the teachers had a PC or laptop for their use at home. Only one teacher out of eleven had ever owned an e-reader. Teaching with technology not practiced enough Only 3 out of the 11 teachers surveyed agreed that they often try to incorporate technology into their teaching. The rest either disagreed or were neutral. This suggests the need or a paradigm shift in terms of teacher attitudes towards technology-assisted teaching and learning. “Boring” books bore students The majority (63%) of the teachers acknowledged that the textbooks they use to teach students were not engaging enough, with 54% of them further stating that students were usually bored with reading their textbooks in class. More interactivity, more focus 64% of the teachers admitted to not being familiar with e-readers in general, but all of them agreed that students’ focus in the classroom would increase if the © 2016 The authors and IJLTER.ORG. All rights reserved.

lessons were more interactive (save for one who remained neutral). Furthermore, all of them (save for two neutral respondents) believed that teaching would be easier if it was done through digital devices such as iPads. To further corroborate the views of the students, every last one of the teachers believed that kids would learn faster if they could immediately look up difficult terms, phrases or concepts online while reading their school books, and that kids should have internet access on such devices. Teaching would be easier on a digital device 91% of the teachers surveyed believed that it would be easier to give and grade homework/assignments on a digital device, and that they would not mind having all their lesson plans, attendance registers, etc. stored digitally on such a device. All of them further agreed that teaching would be easier and faster if everyone in class had an e-reader. More than half of them further disagreed that students would be distracted in class if they had such a device. “Teacher’s Edition” e-readers would be desirable Conclusively, all but one of the teachers (who remained neutral) were in support of having all school textbooks accessible on a digital device, and they expressed a desire for a different “Teacher’s Edition” of such a device, should it be implemented.

Assertions 54%

KIDS WOULD BE DISTRACTED WITH E-READERS

27%

TEACHING WOULD BE EASIER IF DONE ON A DIGITAL DEVICE

18% 82%

STUDENTS WOULD FOCUS MORE IF LESSONS WERE MORE INTERACTIVE

0% 100% 64%

I AM FAMILIAR WITH E-READERS

27%

STUDENTS GET BORED WITH READING BOOKS IN CLASS

27% 54% 18%

BOOKS USED TO TEACH AREN'T ENGAGING ENOUGH

63% 0%

20%

Disagree

Agree

40%

60%

80%

100%

Figure 7: Various assertions among teachers Teachers: General Comments Qualitative data was also obtained from the teachers at the end of the given questionnaire. Comments were mostly supportive of the initiative, and ranged from support of using digital devices such as iPads in schools, to acknowledgement of the success of such initiatives in other countries (one teacher mentioned Sweden in particular). As one teacher put it: “Students

120%

would not be bored (of e-readers), they would enjoy it. Less paper, less usage of exercise and textbooks. Would be ideal.” Table 4: Comparison of findings between student and teacher questionnaire responses Students Teachers Students do not have e-readers, and not all have internet access Students prefer reading from books than from laptops Students like reading in general, but mostly for school Students read for leisure mostly a few times a week Most of the students read on a daily basis

Students mostly read offline Students have low attention spans when it comes to reading Students DO NOT find school work boring, but would focus more if it was more interesting Students would study better if they used electronic devices Students would prefer having their books in digital rather than physical form

Teachers teach several hours a week with short, infrequent reading periods in between Teachers do not often try to incorporate technology into their teaching Teachers acknowledge that “boring” books bore students Students do not bring textbooks to class because they cannot afford them Teachers are not familiar with e-readers, but believe more interactivity would increase focus Teaching would be easier on a digital device Teachers are in support of e-readers, and they would like their own version (“Teacher’s Edition”) -

Findings from the publisher The findings from the interview are presented below.  Poor infrastructure hindering initiatives – In many parts of the country, the availability of basic amenities like electricity mean that students are struggling to make effective use of the physical hard-copy books they already possess. This lack of basic amenities, not to mention an almost total absence of adequate internet access in most private and state schools beyond Windhoek, means that the focus shifts from implementing future-forward technological initiatives (such as ereaders), and remains firmly entrenched on fixing the current ills plaguing our education system.  Social ills reduce quality of education received – The problem is exacerbated by the growing gulf between the rich and the poor, wherein kids from high socio-economic backgrounds can afford to be schooled at private schools where they are afforded adequate school materials, teacher attention and support, as well as the benefit of home-taught reading, writing and comprehension skills. These schools also have the budget to afford luxuries like e-readers in classrooms for their students © 2016 The authors and IJLTER.ORG. All rights reserved.



due to the relatively high tuition fees that they charge. Learners from low socio-economic backgrounds, however, have challenges in buying books, stationery and even basic amenities like healthy, balanced meals. Logistical and regulatory challenges delay service delivery – Publishers in the country serve to accomplish several objectives. One of these is to deliver quality, context-relevant textbooks in designated languages to schools in the country. These tasks are however dependent on the backing and support of the relevant government bodies within the country. Regulatory delays in syllabus approvals for school-taught subjects inevitably lead to printing delays on the publisher’s end. This all cumulatively means that students receive their prescribed school textbooks later than usual, resulting in an inadequate number of study materials for all students. Implementing e-readers would be prohibitively expensive – Furthermore, the funding model that would be required to acquire ereaders (ostensibly to improve the reading skills for every student in every school in Namibia) would run up a bill that does not justify abandoning the poor state of the current reading culture status quo. From their point of view, the interviewee felt that the money that would be spent on such an e-reader initiative could be better channeled towards solving the tangible, urgent problems that we currently face in our education sector. The Namibian consumer market is not yet ready – Moreover, the consumer market in Namibia, from a publisher’s point of view, is not conducive to the sale and use of e-readers, due to high rates of unemployment among the ranks of the parents who would be the buyers of such devices. With time, they think, the situation might improve to the point where having an e-reader is no longer a luxury, but a necessity.

Proposed approach in line with the methodology Defining a framework of stakeholders and roles It was important to identify the main stakeholders within the Namibian education sector. Table 5: Key stakeholders in Namibian education and their envisioned roles Stakeholder Roles/Strategies ● Build up and maintain adequate infrastructure such as ubiquitous electricity coverage and internet access in all schools ● Provide device subsidies to parlay initial costs of device Government acquisition ● Provide teacher ICT training ● Develop syllabi for students ● Liaise with publishers to decide on content for the devices Teachers ● Undergo ICT training for teaching with digital tools ● Design and develop digital content and layout for the devices ● Publish, market and advertise quality content to provide a Publishers plethora of choices for teachers © 2016 The authors and IJLTER.ORG. All rights reserved.

● ● Community Leaders & Administrators ● Software developers ● Students

Engage in cost-effective practices during the publishing process to keep final content costs down Provide awareness of new ways of teaching, provide support and encouragement to schools during transition and liaise with relevant government bodies for national buy-in. Encourage and reward platform developers to come up with innovative apps and other learning tools Design, develop and publish engaging, interactive and educational apps that can be integrated into Namibian schools. For example, software developers different languages Use devices and all apps, tools and resources within the learning ecosystem to improve all necessary metrics such as reading literacy, writing ability, numeracy skills, and subject comprehension.

These roles can play a central role within a larger implementation framework. It is evident from the findings that different factions have different views on the viability and strategy of e-reader implementation in the country. Summary of findings Findings clearly show a huge gap between the different stakeholders, i.e., learners, teachers and publishers. There are a couple challenges which could be social, economic, and technical and ownership of ICT devices that may affect implementation of emerging technologies. Namibia has different cultural backgrounds and many official languages with a population of just over 2 million people. These differences certainly affect implementation of new technologies. However, as technology changes there is need to be innovative and design a strategy that will enable ICT integration in Namibian schools. Hence, the proposed plan in Figure 7. Proposed implementation plan Based on the views of the stakeholders surveyed in this research, it is clear that the coordinated efforts of several stakeholders is paramount to ensuring successful replication of such programs nationwide in primary, secondary and tertiary schools alike. Defining the roles that these stakeholders will play enables the creation of a robust implementation strategy for e-reader deployment. The stakeholders and their concomitant roles are explained in Table 4. Certain key assumptions were made in the creation and definition of these roles. Chief among them was that the key education stakeholders in Namibia would buy into the idea of e-reader deployment across the country. The role-definition process was supported by a careful consideration of existing literature pertaining to ICT implementation in schools, the identification of pivotal stakeholders in the Namibian education sector, the engagement of these stakeholders through qualitative methods and a comparison of findings from the research to the existing literature. The framework in and of itself is meant to act as a guideline for governing bodies that aim to undertake the process of ICT integration in institutions of learning As such, the purposeful non-linear, non-cyclical and non-parallel © 2016 The authors and IJLTER.ORG. All rights reserved.

nature of the framework is designed to allow for flexibility in determining which facet is to be worked on first, last or concurrently with other facets of the framework.

Stakeholder engagement

Monitoring & Evaluation - Stakeholder feedback

- Students - Teachers - Publishers - Schools - Content Providers

ICT Infrastructure

- Regular review against long-term goals

Namibian ICT Integration Framework

Hardware/Software - Networking structure - Content creation - Emerging trends

Awareness, Training & Policy Support - Draft training schemes - Ongoing professional development

New Business Models - Cost structures - Lean production

Figure 8: An ICT plan for implementing new technologies in Namibia The proposed plan is based on the findings from the two studies and observations on the current ICT state in Namibian schools. A brief description of the major components of the ICT integration plan is given below:  Stakeholder Engagement – Stakeholders are one of the key factors of this framework. A far from exhaustive list of this subset would include: Students, Teachers, School Administrations, Publishers and Content Providers. These stakeholders would need to come together to forge a path forward.  ICT Infrastructure – This includes the physical and non-physical aspects. The physical aspect entails the underlying hardware structures, such as the requisite electricity grid coverage and the terrestrial wiring of broadband cables to enable internet connection. Computers, storage devices, electronic tablets fall under here as well. The non-physical aspect of the infrastructure subset deals with the intangible, such as software provisions for the e-readers, cloud storage for schools, and creating language-localized educational material.  New Business Models – ICT investments are capital-intensive, and it is necessary to have an accurate grasp of estimated costs and expected © 2016 The authors and IJLTER.ORG. All rights reserved.



returns on investments (ROIs) in order to ensure sustainable spending practices. Awareness, Training & Policy Support – It is necessary for new implementations of ICTs to be paired with sufficient training to enhance overall integration. This can be achieved through training workshops, seminars and advanced professional development. Furthermore, supporting policies must be enacted to enable and assist the overall process. These include the commissioning of broadband infrastructure by government; subsidized equipment procurement; offering training, professional certification and increased remuneration for ICT-related skills; improved working conditions for affected stakeholders (e.g. teachers), and more awareness campaigns about the benefits of ICTs in schools. Monitoring & Evaluation – After implementation, monitoring and stakeholder feedback solicitation are crucial to determining the success or ineffectiveness of e-reader deployment. These are needed to gauge the effectiveness and efficiency of implemented solutions against long-term goals.

Conclusion The proposed implementation plan requires the establishment of a committee that will be responsible for driving e-reader deployment in Namibian classrooms. This committee should consist of people from different backgrounds who are committed to seeing the proposed idea through. From the findings, it is clear that this will require working together and engaging a lot of stakeholders. The committee will need to comprise of relevant stakeholders from the education sector, as well as from ancillary sectors such as social services, health, sports and culture, the arts and others. The committee will need an established mandate on that covers several facets:  implementation of e-reader deployment  identification of high-need institutions within the country  establishment of supplier, partner and donor relationships with regard to the e-readers and other required resources  ongoing feedback solicitation on the effectiveness of the program, and  long-term scaling of the deployment initiative In this paper we have focused on the findings from the two studies that could assist in identifying the views of the Namibian participants, as well as in designing an ICT strategy. We started out by first looking at the challenges being faced by schools in developing countries, followed by a brief overview of the Namibian education system. This was to allow us to understand the root problems being faced by students and educators alike. A summary of core teaching theories followed, enabling us to put into the context the methodological approach chosen for this study. This approach was described, together with the intervention used. The analysis was performed, and the results extracted from the data. We discovered that, while interest in the deployment of e-readers is high (as we expected), the actual execution could face some challenges, and these were summarized. These findings then properly informed our proposed strategy for implementing our tentative idea: that of e-reader © 2016 The authors and IJLTER.ORG. All rights reserved.

deployment in Namibian schools as a positive way of alleviating some of the challenges being faced in the sector. We aim to share the ICT integration plan during the workshop and learn from other ICT experts as well. References Ballantyne, P. (2004). Evaluation of Swedish Support to SchoolNet Namibia. Development. Sida 2004. Retrieved from www.sida.se/publications Barker, R. (2011). Report of the inquiry into overcoming the barriers to literacy. All Party Parliamentary Group (APPG) for Education. British Educational Suppliers Association (BESA). doi:http://www.educationengland.org.uk/documents/pdfs/2011-appgeliteracy-report.pdf Evans, G.L. (2013). A Novice Researcher’s First Walk Through the Maze of Grounded Theory: Rationalization for Classical Grounded Theory. Retrieved from http://groundedtheoryreview.com/2013/06/22/a-novice-researchers-firstwalk-through-the-maze-of-grounded-theory-rationalization-for-classicalgrounded-theory Fischer, G. (2001). The Namibian Educational System, 1–8. Retrieved from http://www.fesnam.org/pdf/2010/TheNamibianEducationalSystem.pdf Hare, H. (2007). ICT in Education in Tanzania, (July 2007), 1–9. Retrieved from https://www.infodev.org/infodev-files/resource/InfodevDocuments_432.pdf Hovious, A. (2014, June 18). The presumptions, policies and practices that prevent digital and information literacy learning in the classroom. Retrieved June 27, 2015, from Designer Librarian: http://designerlibrarian.wordpress.com/2014/06/18/thepresumptions-policies-and-practices-that-prevent-digital-and-informationliteracy-learning-in-the-classroom/ Herrington, J., McKenney, S., Reeves, T., & Oliver, R. (2007). Design-based research and doctoral students: Guidelines for preparing a dissertation proposal. In C. Montgomerie, & J. Seale (Ed.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2007 (pp. 4089-4097). Chesapeake, VA: AACE. Retrieved July 6, 2015, from http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=2611&context=ecuworks Huitt, W. (2013, December). Summary of theories relating to learning and development. Retrieved July 21, 2015, from Educational Psychology Interactive: http://www.edpsycinteractive.org/topics/summary/lrndev.html Keller, H. (2010, August 22). Technological Literacy: The Key to Education Reform. Retrieved June 27, 2014, from ETC (Educational Technology & Change): http://etcjournal.com/2010/08/22/technological-literacy-the-key-to-educationreform-2/ Ministry of Education. (2008). The development of education: National Report of Namibia, 1–25. Windhoek NIED: Namibia Mehdipour, Y., & Zerehkafi, H. (2013). Mobile Learning for Education: Benefits and Challenges. International Journal of Computational Engineering Research. Motlik, S. (2008). Mobile Learning in Developing Nations: International Review of Research in Open and Distance Learning. Athabasca University: Canada’s Open University Power, T., & Sankale, J. (2009). Mobile technologies: Current practice, future possibilities. In C. Vrasidas (Ed.), ICT for education, development and social justice. Charlotte, NC: Information Age Publishing. Reeves, T., Herrington, J., & Oliver, R. (2004). A Development Research Agenda for Online Collaborative Learning. Educational Technology, Research and Development, 54(4), 53-66. © 2016 The authors and IJLTER.ORG. All rights reserved.

Sommerville, I. (2010). Software engineering (Ninth Edition). Edwards Brothers: Boston. Stork, C., & Calandro, E. (2011). Internet gone mobile in Namibia. Retrieved from https://www.researchgate.net/profile/Christoph_Stork/publication/26336769 4_Internet_going_mobile_internet_access_and_use_in_11_African_countries/lin ks/53ee036a0cf26b9b7dc63f03.pdf Traxler, J. (2005). Defining mobile learning Interactions. Warwick: University of Warwick, Retrieved from http://iadis.net/dl/final_uploads/200506C018.pdf Wilson, N., Zygouris-Coe, V., & Cardullo, V. (2014). Teaching & Learning with E-Readers: Promoting Deep Learning or Deep Trouble? International Reading Association. Retrieved July 22, 2015, from http://www.academia.edu/8921521/Teaching_and_Learning_with_EReaders_Promoting_Deep_Learning_or_Deep_Trouble

International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 65-75, February 2016

Descriptive Study on Grade 2 Pupils Relationship Behavior and School Adjustment As Perceived By Teachers: The Case of Jimma Zone, Oromia FISSEHA MIKRE (Assist/Professor) and NASSER ABA-MILKI (Lecturer) (Department of Psychology, Jimma University, Ethiopia)

Abstract. This research aimed at examining teachers’ perceptions of their relationship with pupils and the association of this relationship with the pupil’s school adjustment. Quantitative data on the teachers’ perceptions of the pupils’ relationship and school adjustment behaviors were collected from 26 self-contained classes for 446 grade two sampled pupils using standardized measures. The Ward’s method of cluster analysis identified the following three distinct pupil- teacher relationships, (a) positively involved, (b) functional average and (c) negatively involved. Likewise, the one way analysis of variance computed for the three relationship behavior scores showed statistically significant variation among the three clusters that designates the presence of three distinct pupil’s relationship behaviors. In addition, the one way analysis of variance for the school adjustment scores among the three relationship types resulted in a statistically significant variation. The pupils whom the teachers reported to have positive relationship show close, warm and interactive relationship behaviors with their teachers. Moreover, the pupils scored significantly higher in school adjustment measure than the pupils whom the teachers reported to have functional average and negative involvement in their relationship behavior. Furthermore, the Pearson Product Moment Correlation analysis between pupil’s relationship behavior and school adjustment scores revealed the presence of a strong positive and statistically significant association between the teacher-pupil relationship and the school adjustment measure. Keywords: Relationship behavior; perceptions; early relationships

school

adjustment;

teacher

Introduction Several developmental theories assert the significant role teacher-pupil relationship play in leading to a range of positive academic and social outcomes (Wentzel, 2009). According to Bergin and Bergin (2009: p141), a child’s school success can be influenced by the type of affection he/she has with parents at © 2016 The authors and IJLTER.ORG. All rights reserved.

home and teachers in the school environment. The same authors assert the importance of early relationship in predicting the long-term well-being of the child. In general, the significance of early year’s relationship behavior to learning and development is a well acknowledged phenomenon. Pupils’ differences in relationship behaviors with adults are linked to the variations in school adjustment and learning. Kamala (2013), for instance, concludes that pupil’s relationship behavior with significant persons predicts their competence in school adjustment. Hamre and Pianta (2001: p636) also confirm teacher-child relationship patterns as greatly useful components of children’s success at school. At the early years, teachers assume a parent-surrogate role for children and may observe relationship behaviors which can have salient contributions for school adjustment and certain developmental outcomes for the child (Ramadass & Gowrie, 2014). There is also a general conviction to the critical nature of early years in human development. Research evidence show the quality of relationships to be linked with the child’s school adjustment behavior at present and in the future (Hughes, Gleason, & Zhang, 2005: p305). In fact, the correlations between quality early relationship and later school work are strong and persistent. The relationship is more evident in the areas of academics and social success (Hamre & Pianta, 2001: p636). Kennedy and Kennedy (2004) indicated the presence of strong conviction on the significance of high quality early affiliation on children’s school adjustment. O’Conner (2007) also indicated the contribution of high quality relations for children’s academic success. From this, one can make an assumption that children’s relationship behavior influence academic achievement through the encouragement of active learning and class activities (Patrick, Mantzicopoulos, Samarapungavan, & French, 2008). Secure teacher-pupil relationships may be significant to make the school a supportive environment that can influence the adjustment competence of pupils. Moreover, when children experience positive relationships at school, they act attentively and explore their environment well. On the other hand, the experiences of insecure relationships with teachers lead to stress, suspicious exploration of the school environment and distorted self-concepts (Wentzel, 2009). In general, secure relationship forecasts more knowledge, high test result, learner motivation and fewer problematic and special needs education (Bergin & Bergin, 2009: p154). Negatively involved type of pupil relationship is characterized by continuous controlling of children’s behavior and discouragement of the teacher in creating positive classroom setting (Driscoll & Pianta, 2010). The major predictors of pupil insecure relations and maladjustments may be attributed to some unfulfilled or thwarted pupil needs within their homes and/or school environment. Teachers’ sensitivity to the type of relationship behavior determines the quality of school adjustment and learning for the child. It has also been estimated that 12 percent of the world’s primary school going children are so emotionally upset as

to require the services of educational psychologists, sociologists or guidance and counseling specialists in matters of relationship and emotional stability (Ramadass & Gawrie, 2014). Hence, this is contextually a timely study with the intention of describing the teacher-pupil relationship behavior and its association to the pupils’ school adjustment competence as perceived and reported by the teacher. Such type of research evidence can be informative for those significant individuals such as school teachers and school psychologists to understand how patterns of relationship behavior determines school adjustment and competence in the school environment and help to prepare themselves for possible interventions for perceived problematic relationships as the early relationship experiences have paramount importance for the individual’s future life.

Teacher-Child Relationships Research findings showed positive relations between teacher–learner interaction and their school performance and adjustment (McCormick, O'Connor, Cappella & McClowry, 2013). Relationships are the arenas for socialization, development of communication skills and the regulation of emotions for children (Driscoll & Pianta, 2010). A secure and close type of relationship not only predicts school adjustment but also crucial to the development of later successful relationship. Children adjust well if they feel their relationship is emotionally supportive (Wentzel, 2009: p309). On the other hand, if they feel threatened, anxious or uncertain, they fail to adjust well at school. The role of school teachers is not only to facilitate for knowledge acquisition but also socialize the children to form trusting relationships with others. As Vygotsky (1978) stated it the teacher-child relationship behavior and the perception of the relationship by the teacher exert influence on salient developmental outcomes including cognitive ability. Children, who are supported for independence, motivated for achievement and encouraged to feel worthy, differ from their classmates on later quitting of school, success in learning and peer social skills in the school context. Bergin and Bergin (2009: p141) asserts the crucially of socio-emotional wellness on success at school where the basis of which is early attachment and relationship behaviors. There are several studies which document teachers’ perceptions on children’s relationship behavior. Pianta (1997: p15), in his research described six categories of teacher relationship perceptions of children as uninvolved, dependent, angrydependent, dysfunctional, functional average and positively involved positively involved. Children in the different patterns of relationships vary for the school adjustment measure. Of these, the most problematic are the dysfunctional and the angry-dependent. The functional average and positively involved children show relatively good adjustment to the school environment. They also show the fewest problem behaviors at school. Children whose relationships are described as dependent and angry dependent often experience adjustment difficulties at school. They have more conduct problems, less competent in cognitive functioning and also less tolerant to frustrations. Developmental researches have also documented angry–dependent relations at early childhood period to be

associated with decreased competence in socio-emotional functioning of the child. According to Demaray and Malecki (2002: p213), pupils with low perceived support attained significantly lower scores on positive behavior indicators and higher scores on problem behavior indicators than those having average or high perceived support groups do.

Child-Adjustment at School A well-adjusted child at school shows more behaviors of independence, creativity, active involvement in school work and less irritable behaviors. Kington (2013: p117) asserts higher levels of school adjustment and competence to have bases from positive teacher-pupil relationships and negative relationships to predict less promising path for children’s future. Childadjustment at school correlates with the relationship behavior of significant others such as the school teacher. For instance, Patrick, et al (2008: p126) and Furrer and Skinner (2003: p149) claim that having a relationship with one’s teacher characterized by closeness, absence of conflict or dependency increases the chance of pupil motivation and achievement at school. On the other hand, children with anxious, avoidant and negative relations with teachers often show adjustment difficulties. For instance, children who are identified by dysfunctional and angry dependent relationship behaviors likely show more conduct problems, limited cognitive competence and learning difficulties. In fact, children with different relationship patterns with teachers vary in school adjustment behavior. Children who often show positive relations exhibit better habits in various school works. There are researcher evidences which report the social adaptation advantages of early relationship behavior of children (Hamre & Pianta, 2001: p626). The teacher’s perception and care for the child’s emotional needs plays a salient role to predict learning and the development of social skills. Teachers are expected to examine the classroom environment in such a way that children are treated well and cared for. In the words of Malecki and Demaray (2003: p249) emotionally supportive tendencies of teachers relate to the children’s academic success to a great extent. As a result of this, the influences of relationship behaviors on school adjustment should receive the highest recognition to be investigated so that to pave the ways for intervention schemes in case of problematic adjustment patterns. Because, improving the quality of teacherpupil relationship starting from kindergarten and early grades can have salient contributions to the effectiveness of schools (Pianta, Hamre, & Allen, 2012: p336).

Research Methods This study followed a cross-sectional survey design that was helpful to collect data on grade 2 self-contained classroom teachers’ perceptions of children’s relationship behaviors and the corresponding adjustment at school. Twenty six grade 2 self-contained teachers from four Districts of Jimma Zone filled out the adapted teacher-child relationship scale a seminal work of Pianta and Steinberg (1992) and the school adjustment scale by Barbara (1975) for a total of 446 children. Before the actual data collection, the two instruments were checked for

content validity to examine whether they can reliably measure the intended variables in the study. A pilot-test of both instruments by five teachers for twelve children each resulted in an internal consistency reliability coefficient of 0.76 for the teacher-child relationship scale and o.69 for the child’s school adjustment scale (which can be judged as moderate). The data for the main study were collected on separate days for the two scales. The twenty six grade two self-contained teachers filled out the teacher-child relationship scale for an average of eighteen children each. After two weeks, they again filled out the school adjustment scale for the children to whom they filled the teacher-child relationship scale. The time gap in filling out the two scales helped to decrease the chance of bias and maximize the return rate of the scales. The responses were based on a 5 point Likert scale ranging from definitely does not apply (1) up to definitely apply (1) to the child yielded a range of scores from 21 to 105 for the teacher-child relationship scale and from 19 to 95 for the school adjustment scale, respectively. In both types of scales relatively high scores show positive and relatively low scores show negative outcomes in the measured variable. After assigning numerical values to both types of measured variables (N= 446, Female= 218 & Males=228) the Ward’s method of cluster analysis was done for the teacher-child relationship behavior scores. Ward’s hierarchical method of cluster analysis is based on the logic of minimum error variance grouping (SAS Inc., 2008). In the clustering, three distinct cluster solutions came out for the teacher perceptions of children’s relationship behavior. Following the clustering, the school adjustment scores of each child were matched to the scores of teachers’ perceptions of child relationship behavior for the respective clusters. Next, a one way analysis of variance that assumes inequality of variation for teacher relationship perception scores and school adjustment scores among the three cluster solutions was computed to verify whether the three patterns of relationships are equally homogeneous for the two measured variables. Then after, a mean difference test (t-test) that assumes the three patterns of relationship perceptions as independent was computed for both relationship perception and school adjustment variables. Further, to check for the presence of systematic association between the two variables, Pearson-Product-Moment correlation was calculated for the three clusters. Finally, the statistical tests of significance in the study were all checked at alpha (α) = 0.05.

Results The Ward’s hierarchical cluster analysis method carried out on the raw scores of child relationship behavior obtained from 446 sampled children resulted into three distinct teachers’ perceptions of the pupils’ relationship behaviors as perceived by their self-contained classroom teachers. This method works by iteration of the scores to reach to the final cluster solution, where the researchers chose the clustering with the least error variance grouping. After checking the cluster solutions for 3, 4, 5 and 6 groups, the minimum error variance was found to be for the cluster solution of 3 groups. Therefore, the researchers decided the

three cluster solution to report the results. Table 1 below shows the number of observations (n), mean scores (X) and standard deviations (SD) of the different relationship behaviors. Table 1: Number of observations, mean score and standard deviation in the relationship score

Cluster case

Observations(n)

Positively involved Functional average Negatively involved

156 182 108

34.97 40.81 24.22

Mean Score(X) 95.26 80.21 65.88

Standard Deviation(SD) 4.81 4.74 4.68

Table 1 shows the three types of relationship behaviors as perceived by their self-contained classroom teachers, namely the positively involved (n=156), functional average (n=182), and negatively involved (n=108). This classification was made by assuming the least error variance grouping. The one way ANOVA that assumed homogeneity within the same cluster case was carried out on the three clusters of pupils’ relationship behaviors as perceived by their teachers (see table 2). The Leven’s test for inequality of variances among the three groups also confirmed the presence of significance variations on the pupils’ relationship behavior perceptions of the teachers for the three distinct clusters. Table 2: ANOVA Summary for the three pupil relationship behavior types

Variations Between groups Within groups Total ** P< 0.01

SS 29 999.72 21564.86 51459.58

df 2 444

MS 14999.36 48.46

F-ratio 309.52**

Table 2 shows the presence of a statistically significant variation of the teachers’ perceptions towards the relationship behavior of children in the three cluster cases (F 309.52, df (2/444), P<0.01). This result depicts the presence of three distinct teacher-child relationship patterns as perceived and reported by the teachers. Table 3: Number of observations, mean score and standard deviation in the school adjustment behavior

Cluster case

Observations(n)

Positively involved Functional average Negatively involved

156 182 108

34.97 40.81 24.22

Mean Score(X) 90.47 77.96 62.38

Standard Deviation(SD) 5.11 4.86 4.52

Table 3 above shows the three groups of pupils’ adjustment situations at school, where the well-adjusted are (n=156), moderately adjusted (n=182), and poorly adjusted (n=108).

Table 4: ANOVA Summary for pupil’s school adjustment types

Variations Between groups Within groups Total P<0.01

SS 22168.74 21986.62 44155.36

df 2 444

MS 11849.37 48.77

F-ratio 223.65**

On the other hand, one way ANOVA was conducted on school adjustment scores for children grouped in the different relationship patterns as perceived by their teachers (see table 4).As shown in the table, the F-statistic resulting from the one-way analysis of variance revealed the presence of statistically significant variation (F=223.65, df (2/444), P<0.01) in their school adjustments. This result showed statistically significant difference in the school adjustment scores where the positively involved receiving high scores, which show better adjustment in the school environment to benefit from academic learning and social competence. Furthermore, Pearson Product Moment Correlation that assumes both relationship and school adjustment behaviors of children as continuous variables computed & shown in table 5 below. Table 5: The correlation between pupils’ relationship and school adjustment scores

No 1 2 3 4

Case Whole group Positively involved Functional average Negatively involved ** P< 0.01 * P< 0.05

N 446 156 182 108

Pearson Correlation Coefficient 0.83 ** 0.74** 0.58* 0.42*

As indicated in table 5, the correlation analysis showed the presence of strong and statistically significant links between the relationship behavior of pupils as perceived and reported by the teachers and the corresponding school adjustment scores (P<0.001). The correlation coefficient values reveal that there are associations between teachers’ perceptions of pupils’ relationship behavior and measures of school adjustment which range from light to strong, respectively. For instance, for the positively involved relationship group, the correlation coefficient value is 0.74 that shows the presence of a strong positive association between the teachers’ perception of the children’s relationship behavior and the school adjustment score.

Discussion Current researches are showing the significant role of relationship behaviors to children’s school adjustment and academic performance. Driscoll and Pianta (2010: p40) witnessed the presence of evidence in support of the link between pupils’ school adjustment and the importance of teacher-pupil relations in the early elementary school years. As Murray-Harvey (2010:p104) avers, compared to the relationships with family and peers, teacher-pupil relationship exerts the strongest influence on academic, social and emotional outcomes. The salience of

early adult-child relationship and the perceptions associated to children’s learning and development is also a well acknowledged fact (Ramdass & Gowrie, 2014). According to the perceptions of teachers, grade two pupils in the present study were classified into three distinct relationship clusters as of children with positive involvement (secure, affectionate and warm), positive but moderate involvement (functional average group) and negative involvement (conflicting, avoidant and dependent) respectively. Similar results about teacher-child relationship behaviors at Kindergarten level were already reported in several studies (Driscoll & Pianta, 2010). The teachers’ perceptions clearly revealed those children in the positively involved relationship cluster are often characterized by close and warm relationship behaviors. Most of the teachers reported to experience a warm, secure and a relatively affectionate relationship with the children. Moreover, relationship items indicating conflict and dependency are rated the lowest among these children. The moderately positively involved children’s relationship behavior was reported to be in mid-way between positive and negative experiences. The children who are characterized to have negative relationship patterns with their teachers often show conflicting, avoidant and dependent relationship patterns (Bergin & Bergin, 2009). Since the importance of early life in general and relationship experiences in particular is well supported by development theories and practices in the field, the findings of this study can have clear implications for further rigorous research and inform the practices on the part of early childhood caregivers and teachers. On the other hand, the study finding revealed the presence of a strong association between children’s relationship behavior as perceived by the teachers and the school adjustment scores. The more the child is positively involved his/her relationship with the teacher, the more he/she will likely to experience successful and competent adjustment behaviors in the school environment. On the other hand, when teachers perceive positive relationships, they tend to exert more effort to guide and to teach, and the pupils in turn develop trust and motivated to succeed (Driscoll & Pianta, 2010: p40). Furthermore, the well-adjusted children outperform their class mates in academic competence, peer relationship, maturity and also language development. For instance, a study by McCormick et al (2003: p611) reported a valid prediction of high quality teacher-pupil affiliations at Kindergarten level and in first grade Mathematics achievement. For the insecure children, there are conditions in the environment which create frustrations leading to personal inadequacies, feelings of inferiority, rejection by teachers, parents or peers. In many respects, these conditions happen to relate to conflicting and dependency oriented patterns of child relationship behavior. © 2016 The authors and IJLTER.ORG. All rights reserved.

Hence, caregivers and teachers at the early periods of life would need to be sensitive and skillful to identify patterns of early childhood relationship behaviours as this may facilitate to early intervention and the devising of copying strategies when the child grow up. Thus, teachers would be able to foster positive relationships, which are predictors of pupils’ academic success, active engagement and enthusiasm about learning (Reyes, Brackett, Rivers, White & Salovey, 2012: p701). In summary, perceived positive relationships of pupils are capable of boosting the teachers’ motivation to extend their effort and time to enhance the pupils’ successful and competent adjustment behavior in the school setting. This, in turn will lead to eventual improvement in the academic performance of the pupil. Contrary to this, conflict and dependency based relationship behaviors may potentially hamper the attempts of creating a positive classroom environment (Wentzel, 2009).

Conclusion Childhood social environments can have association with certain developmental outcomes such as adjustment at school and learning competence. For instance, teacher-child relationship behavior associates with the child’s social, emotional and academic development outcomes. As this study showed significant variations exist in the way school teachers perceive the pupils’ relationship behavior. These significant variations in the relationship behavior are also strongly linked to the pupils’ adjustment in the school environment. The significance of childhood life experiences to the betterment of later development and life is a well theorized and evidenced phenomenon. Specifically, there is a strong conviction to the prominence of early relationship experiences to the acquisition and development of competent behaviors, which will contribute to an individual’s quality of life in later periods of life. Because of this reason, teacher-child relationship patterns at early grades would require careful observation and study with the intention of informing school personnel particularly the teachers and promoting positive early social relations and school adjustment for a scheme of not only encouraging the positive relationships involvement and adjustment but also to plan for remedial interventions for children with problematic social relationships and incompetent adjustment at school and with difficulties in successful learning.

Recommendations Early life social processes particularly childhood relationships behavior with significant others have great implications for school adjustment and other desirable developmental outcomes. Consequently, it is essential to note down the fact that significant influence of social processes in children’s adjustment, learning and development. Therefore, the following recommendations are forwarded:  Teachers at the early grade levels need to get refreshment training in how to identify children’s relationship behavior and approach the children by considering social and emotional tendencies.

 Teachers at the early grades are required to be attentive in identifying the children’s relationship behaviors to facilitate intervention mechanisms with children of problematic behavior.  Teachers in collaboration with school psychologists and parents of the children may intervene on the children with problematic relationship patterns because early year interventions are likely to bring better outcomes of school adjustment and social relations.  Researchers in the areas of school psychology shall pay greater attention in furthering investigations which will come out with better knowledge of children’s relationship and school adjustment behavior so that to inform teaching at early grades, teacher professional competence and responsibility.

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International Journal of Learning, Teaching and Educational Research

Vol. 15, No. 2, pp. 76-93, February 2016

The Magnitude of Teacher Expectation Effects: Differences in Students, Teachers and Contexts Zheng Li College of International Studies, Southwest University, Chongqing, China

Abstract. This article aimed to present a comprehensive review of the moderators of teacher expectation effects.

It concluded the factors

which may strengthen or weaken the effects of teacher expectancies in classrooms. Apart from student characteristics, this article highlighted the individual differences in teachers and contextual features which have not been systematically reviewed to date. It seemed that some teacher and contextual variables were likely to generate and modify teacher expectation effects to a significant extent.

Implications and future

research direction were also discussed. Keywords: Teacher expectation effects, Teacher beliefs, Moderation Effects, Individual differences

Introduction With the publication of Pygmalion in the Classroom (Rosenthal & Jacobson, 1968), the self-fulfilling prophecy theory was acknowledged within educational psychology. In the classic Pygmalion experiment, it seemed that the students (randomly selected) whose teachers were induced to hold high expectations for tended to show greater gains in IQ than control group students one and two years later. The Pygmalion study immediately provoked extremely controversial reactions. Advocates accepted the findings enthusiastically and praised the study as the key to eliminating educational and social inequalities (see Spitz, 1999; Wineburg, 1987 for reviews). However, among some researchers studying educational psychology and intelligence, the experiment generated a storm of criticism (see Spitz, 1999 for a review). After a large number of replication studies examining teacher expectation effects (TEEs) on ÂŠ 2016 The author and IJLTER.ORG. All rights reserved.

students’ IQ, academic and social outcomes in both laboratory settings and real classrooms (see reviews by Brophy & Good, 1974; Hall & Merkel, 1985; Spitz, 1999), the debate came to an end, as Rosenthal’s series of meta-analyses finally demonstrated the existence of TEEs (Rosenthal, 1968, 1974, 1976, 1985; Rosenthal & Rubin, 1978; Rosenthal & Rubin, 1971). The meta-analyses examined studies of interpersonal expectancy effects in laboratory and everyday situations, and revealed that overall 34–40% of the previous expectation effect studies had reported significant self-fulfilling prophecy effects, with the percentage of positive results being slightly higher in the classroom studies than in laboratories. These data and other reviews (e.g., Brophy, 1983; Jussim & Harber, 2005; Raudenbush, 1984) have supported the existence of TEEs and the concept that teachers’ initial expectations increase the probability of students conforming to meet the teachers’ perceptions and predictions. Though it has been acknowledged that self-fulfilling effects of teacher expectations do exist, there have been concerns about the strength of TEEs in naturalistic classrooms. Some research argued that the magnitude of TEEs was relatively small. For example, Brophy and Good (1974) reported that the effects of teacher expectancies averagely contributed to only 5–10% differences per student on academic achievement, and Cooper and Good also stated that there was relatively little evidence in favour of sizeable self-fulfilling effects of teacher expectations (Cooper, 1979; Cooper & Good, 1983). However, researchers have also contended that stronger TEEs may be found in particular classrooms (e.g., Raudenbush, 1984), suggesting that the magnitude of TEEs varied by different teachers, students, classrooms or other circumstances.

Student Moderators of Teacher Expectations Effects In terms of student moderators, findings have shown that students with specific

characteristics are more susceptible to TEEs. These characteristics include student individual differences in race, socioeconomic status, gender, age, prior achievement and so on. Student ethnic group Jussim and colleagues (1996) found that teacher expectations influenced the standardised test scores of African Americans (β = .37) more strongly than they influenced the scores of European American students (β = .14). Steele (1992, 2003) also conducted studies primarily on African American students and argued that they were more susceptible to TEEs than their European American counterparts. McKown and Weinstein (2002, 2003) investigated the role that student race may play as a moderator of the relationship between teacher expectations and student mathematics and reading achievement and they found that African American children were more vulnerable to stereotype threat and © 2016 The author and IJLTER.ORG. All rights reserved.

TEEs, especially negative expectancy effects, than other student groups, for instance Caucasian children. In New Zealand, researchers (Rubie-Davies, Hattie, & Hamilton, 2006) have also reported that Māori students were more subject to unfavourable TEEs than other ethnic groups. More recently, one study about children from kindergarten to sixth grade in Europe (Speybroeck et al., 2012) documented differing associations between teacher expectations and student mathematics achievement for ethnic minority and majority children, and the findings showed TEEs seemed to be somewhat stronger for ethnic majority students (β = .16) than for ethnic minority students (β = .11). Generally, previous research has concluded that expectancy effects are more powerful among students who are from ethnic minority groups. The latest research (Jacoby-Senghor, Sinclair, & Shelton, 2016) has also provided evidence that teachers’ biased expectations may predict black students’ underperformance. In most cases, ethnic minority students may be particularly likely to suffer negative self-fulfilling prophecy effects of teacher expectations.

Student socioeconomic status Investigation of students from lower socioeconomic status (SES) groups whose family has a low income and poor education background has shown that low SES students may be more vulnerable to TEEs, with standardised coefficients of .11 relating teacher expectations to student future achievement for higher SES students, and .25 for students from lower SES backgrounds respectively (Jussim et al., 1996). Another longitudinal study (Alvidrez & Weinstein, 1999) explored the relations between preschool teacher expectations and student high school performance and found that teacher predictions were weakest for students with higher SES families. Another study (Hinnant, O’Brien, & Ghazarian, 2009) about teacher expectations in the early school years as a predictor of future academic achievement in the reading and mathematics domains investigated nearly 1000 children and families at first, third and fifth grades. The findings showed that teacher expectations seemed to be significantly and positively predicting subsequent mathematics performance of children from families low (β = .20, p < .001) and average incomes (β = .12, p < .01) families. However, teacher expectations tended to be not significantly linked to later mathematics achievement of students from high income families (β = .04, p > .10). More recent studies have also reported consistent results of the student SES moderator. For example, one study (Gregory & Huang, 2013) about teachers’ college-going expectations and student postsecondary education status collected data from more than 4000 tenth-grade students and their teachers and parents, which found that teacher expectations had the strongest link to post-secondary education for lower income students. Sorhagen’s study (2013) also used prospective longitudinal data to examine the associations between teachers’ inaccurate © 2016 The author and IJLTER.ORG. All rights reserved.

expectations in first grade and students’ high school performance at age 15; the findings suggested a significant interaction between teacher expectations and student family income, with stronger TEEs on mathematics, reading comprehension, word knowledge and verbal reasoning scores of children from relatively poorer families. Findings have consistently shown that students from lower SES families may be more susceptible to expectancy effects and therefore more likely to conform to what their teachers expected.

Student gender Previous studies have shown that female students may be more vulnerable to teachers’ stereotyped expectations in mathematics, especially when they themselves have incorporated this stereotype into their own views (Eccles & Hoffman, 1984; Eccles & Jacobs, 1986; Meece, Parsons, Kaczala, & Goff, 1982). However, Jussim and colleagues (1996) conducted a study which examined nearly 2000 students in seventh-grade mathematics classes, and documented that girls’ scores were not significantly affected by teacher expectations for their talent more than boys’ were; the predictive effects of teacher expectations on both boys’ and girls’ later scores in mathematics were comparatively small (.10 to .20). Hinnant and colleagues’ work (2009) found that first-grade teachers’ expectations were consistently related to ethnic minority boys’ reading scores in their third-grade, but not to ethnic minority girls’. A more recent study (Wood, Kurtz-Costes, & Copping, 2011) into African American students found that for boys, but not girls, educational attainment expectations made a significant contribution to their post-secondary progress, with eleventh-grade teacher expectations predicting college attendance one year after high school graduation. An investigation (Karwowski, Gralewski, & Szumski, 2015) revealed that the relationship between teachers’ expectations of student creativity and students’ creative self-perception was markedly stronger for female students and males. It seemed that student gender generally was reported as a moderator of TEEs. However, the gender moderator functioned in a complicated manner; it seemed to interact with some other variables, like subject and student ethnicity.

Student age It has been commonly acknowledged that student age works as a moderator of the TEEs mechanism, which indicates that stronger TEEs may occur for children at earlier ages. In the classic Pygmalion study, Rosenthal and Jacobson (1968) evidenced that students of younger ages would be more likely to be affected by TEEs than older students. Later studies confirmed that assumption (e.g., Kuklinski & Weinstein, 2001; Weinstein, Marshall, Sharp, & Botkin, 1987; West & Anderson, 1976). For example, Kuklinski and Weinstein’s study (2001) reported a significant age-related decline in the impacts of teacher expectations on student © 2016 The author and IJLTER.ORG. All rights reserved.

future achievement, and this outcome may suggest that TEEs tend to magnify children’s performance gap in the early grades but gradually diminish in later grades.

Student prior achievement In Madon, Jussim and Eccles’ study (1997) of naturally occurring effects of teacher expectancies, evidence showed that teacher perceptions were more precisely connected to student future achievement for low achieving students than for high achievers. The authors (Madon et al., 1997) argued that low achieving students may ―find school consistently difficult and unpleasant‖ (p. 793), and their greater susceptibility to both positive and negative teacher expectations may result from their lower self-concept (Jussim, 1986), which may lead to greater likelihood of internalising their teachers’ expectations. A more recent study conducted in the Netherlands (de Boer, Bosker, & van der Werf, 2010) explored the relationship between teacher expectation bias—―the difference between observed teacher expectations and predicted teacher expectations on the basis of students’ talent, effort and achievement (p. 169)‖— and long-term student later achievement. The findings of the study (de Boer et al., 2010) demonstrated that teacher expectations, positive or negative ones, were more closely related to low-achieving student performance after one year; however, TEEs were stronger for high-achieving students’ performance after five years. Another study (Archambault, Janosz, & Chouinard, 2012) reported different results; it was found that teacher expectancy effects on student academic accomplishment in mathematics one year later were similar for all students regardless of their prior grades. However, the results may be not representative because the samples for this study were all from schools serving low SES students. In general, student susceptibility to TEES may vary as a function of their prior achievement. Although some studies present different and even contradictory findings, they appear to suggest that the moderation effects of student prior achievement may be influenced by other factors as well (e.g., student SES), which calls for more intensive investigations.

Other student personal characteristics Other student personal characteristics, such as motivation, attribution pattern (Brophy, 1983), and self-concept (Madon et al., 1997), have also been found to moderate TEEs. Students who are more motivated are more prone to TEEs (Brophy, 1983). Students who attribute their success at least partially to their own efforts are more vulnerable to TEEs than students who attribute success completely to uncontrollable factors such as ability or luck (Brophy, 1983). Teacher expectations produce considerably stronger impact for students with lower self-concept in mathematics than students with higher self-concept © 2016 The author and IJLTER.ORG. All rights reserved.

(Madon et al., 1997). When students desire to initiate friendly social interactions with teachers, they are more likely to conform to what their expect from them (Snyder, 1992).

Teacher Moderators of Teacher Expectation Effects Susceptibility to TEEs is also an individual variable in teachers (Brophy, 1983). TEEs are more likely to occur to some teachers with particular characteristics.

Proactive, reactive and overreactive teacher Based on teachers’ behaviour towards students’ previous and current performance, Brophy and Good (1974) hypothesised teachers as being proactive, reactive, or overreactive. Proactive teachers, who were most likely to have positive expectation effects on students, performed their own analysis of their students’ characteristics and needs, had well-articulated ideas about what and how to teach, and consequently shaped students through teachers’ expectations rather than through other sources (Brophy, 1983). According to Brophy and Good (1974), most teachers were reactive and had few self-fulfilling prophecy effects on students. Reactive teachers held their expectations more lightly, adjusting them to respond to new feedback and emerging trends. However, overreactive teachers, according to the authors (Brophy & Good, 1974), usually developed and maintained rigid, stereotyped expectations of students based on student prior records or first impressions, and treated students as stereotypes when interacting with them. These overreactive teachers were most likely to foster undesirable expectation effects in low achievers. The proposal of proactive, reactive and overreactive teachers lacked empirical evidence, however. The authors hypothesised such teacher groupings on the basis of speculated teacher responses to students’ prior records and present behaviour. In their studies (Brophy, 1983; Brophy & Good, 1974), teachers’ expectations, teaching behaviours and the effects on student outcomes were not measured or recorded at all, but the speculations about teacher individual differences shed light upon teachers’ susceptibility to TEEs.

High bias and no-bias teachers Babad and his colleagues distinguished teachers as high bias teachers and no-bias teachers and explored the features of teachers with different susceptibility to biasing information (Babad, 1979; Babad, Inbar, & Rosenthal, 1982a, 1982b; Babad & Inbar, 1981; Babad, 2009). Babad (1979) devised a performance measure to identify teachers who were prone to demonstrate expectancy effects in the classrooms. In this measure (Babad, 1979), students of a physical education college were asked to score two drawings which they were told were drawn by a high SES and a low SES child (based on ethnic and socioeconomic information © 2016 The author and IJLTER.ORG. All rights reserved.

provided about the two imaginary children). In fact, the two pictures were reproduced from a test manual and the drawing created by the so-called ―high SES child‖ had a test manual score three points higher than the one by the ―low-SES child‖. The differences between the scores given to the two children by the subjects (minus the three-point objective difference) were interpreted as the scorers’ susceptibility to biasing information. Unbiased teachers were not easily influenced by social status information in grading students’ assignments, but highly biased teachers assigned notably higher scores to high SES students than to students with low SES. In a series of experimental studies conducted among physical education pre-service teachers (Babad, 1979; Babad et al., 1982a, 1982b; Babad & Inbar, 1981), Babad and colleagues reported stable distributions of bias scores for the student teachers, with one sixth of the subjects scoring the drawings objectively, half mildly biased, and one fourth highly biased (Babad, 1998). Substantial differences were found between unbiased and highly biased individuals. Although highly biased teachers, not the unbiased ones, were more likely to describe themselves as over-reasonable, highly objective, logically reasoned, and unbiased (Babad, 1979), they used more dogmatic statements in written analyses of educational events and manifested more dogmatic behaviours, while no-bias teachers behaved towards students in a more democratic, balanced, flexible, and open manner (Babad & Inbar, 1981). Highly biased teachers held more strongly expressed political views (Babad, 1979) and educational beliefs (Babad, 1985) and exaggerated much more the achievement difference between high expectation students and low expectation students (Babad, 1998). Unbiased teachers perceived and predicted more accurately the differences between students, while highly biased teachers treated different students with different degrees of friendliness, different motivational strategies, and different degrees of criticism (Babad et al., 1982a). Highly biased teachers demonstrated more nonverbal leakage indicating expectation and affect cues towards their classrooms than unbiased teachers (Babad, Bernieri, & Rosenthal, 1989a, 1989b). Most importantly, teachers’ differing susceptibility to biasing information may lead to varying probability of generating TEEs (Babad, 2009). Highly biased teachers created more substantial negative expectancy effects on their students than unbiased teachers (Babad, 1985; Babad et al., 1982a). The series of studies by Babad and colleagues (Babad, 1979, 1985; Babad et al., 1989a, 1989b; Babad et al., 1982a, 1982b; Babad & Inbar, 1981(Babad, 2009)) demonstrated teachers’ susceptibility to biasing information and their subsequent differential treatment towards students. Limitations of their studies were that the participants were not in-service teachers but student teachers, the studies mainly focused on a single subject, physical education, and scorers’ expectation biases were manipulated by the experimenters rather than naturally occurring. © 2016 The author and IJLTER.ORG. All rights reserved.

High differentiating and low differentiating teachers Another major teacher moderator that has been investigated is the extent to which teachers are perceived to treat students differentially (Brattesani, Weinstein, & Marshall, 1984; Weinstein, Marshall, Brattesani, & Middlestadt, 1982; Weinstein, 2002). In a series of studies of children in elementary schools (Weinstein, 2002; Weinstein et al., 1982; Weinstein et al., 1987; Weinstein & Middlestadt, 1979), Weinstein and colleagues developed an instrument, the Teacher Treatment Inventory (TTI), in which children independently reported on the frequency of a variety of teacher behaviours towards an imaginary high and low achiever respectively in their classrooms, and thus perceptions of teachers’ differential treatment were reflected in the difference between the ratings towards those two hypothetical ―students‖. Consistent reports of teacher differentiating treatment supported the classification of high differentiating teachers and low differentiating teachers (Weinstein et al., 1982), and classrooms may be also ―characterised by the degree to which teachers are perceived to differentiate their behaviour‖ (Weinstein & McKown, 1998, p. 220). Studies linking teacher expectations to student outcomes (Brattesani et al., 1984; Kuklinski & Weinstein, 2001; Marshall & Weinstein, 1986; McKown & Weinstein, 2008) showed stronger relationships between teacher expectations and subsequent academic, social and emotional outcomes of students in classrooms with high levels of perceived teachers’ differential treatment. Statistical analyses reported that in classes of high differentiating teachers, 9–18% of the variance in student achievement could be explained by teacher expectations, while the figure dropped to 1–5% in classes of low differentiating teachers (Kuklinski & Weinstein, 2001). Weinstein and colleagues’ work (e.g., Brattesani et al., 1984; Kuklinski & Weinstein, 2000, 2001; Marshall & Weinstein, 1986; McKown & Weinstein, 2008; Weinstein, 2002; Weinstein & Middlestadt, 1979) has contributed to further understanding of the teacher’s role in moderating TEEs. Their findings provide evidence that TEEs in natural classrooms are associated with teacher individual characteristics and the degree of differential treatment of students; however, the studies were mostly conducted in reading classrooms at elementary schools, which indicates a need for investigations within different samples.

High expectation and low expectation teachers In more recent studies, Rubie-Davies has explored teachers’ class-level expectations and pointed out that teacher expectations can be class-centred as well as individually centred (Rubie-Davies, 2004, 2006, 2007, 2008a, 2008b; Rubie-Davies, Flint, & McDonald, 2012). Rubie (2004) identified teachers who held uniformly high or low expectations for all the students in classes. One © 2016 The author and IJLTER.ORG. All rights reserved.

month into the school year, teachers were asked to predict their students’ academic achievement at the end of the year on a seven-point scale. These predicting scores were compared with students’ actual running records at the beginning of the year. According to the differences between teachers’ prediction and students’ actual performance, teachers were identified as high or low expectation teachers who had expectations that were significantly either above or below students’ actual achievement. Data were reanalysed and showed that teachers’ expectations were pervasive for all the students in the identical classroom. When teachers had high expectations for the high achieving students, they were likely to have similarly high expectations for the average and low achieving students in the same class; likewise the low expectation teachers held uniformly low expectations for all achievement levels. Through teacher interviews, and classroom observations, Rubie-Davies found that high expectation teachers and low expectation teachers differed greatly in their pedagogical beliefs and instructional practices (Rubie-Davies et al., 2012), provided varying learning opportunities, and created a diverse socioemotional climate in classrooms (Rubie-Davies, 2004, 2007, 2008a, 2008b). After one school year, students with high expectation teachers made markedly more academic gains than the peers with low expectation teachers did (Rubie-Davies, 2004, 2007, 2008a). In addition, students’ self-perceptions in both academic and non-academic areas were also found to be associated with teachers’ class-level expectations (Rubie-Davies, 2004, 2006, 2008a). Although no statistically significant differences in student self-perceptions were identified at the beginning of the school year, statistically significant differences were found at the end of the school year, because the self-perceptions of students with low expectation teachers declined substantially after one school year. Rubie-Davies’ work about teachers’ uniform expectations for the overall class, and the effects on the overall class outcomes added weight to the argument that TEEs may be a function of individual differences in teachers, especially in their beliefs (Rubie-Davies et al., 2012). Her work identified the teachers who were more likely to enact expectancy effects on the whole class, and suggested possible mechanisms for such effects. However, a larger sample size is needed to enable generalisation of the results. Further, Rubie-Davies’ studies were conducted in reading and physical education courses in elementary schools, which left other subjects and school levels unexplored.

Situation Moderators of Teacher Expectation Effects Teacher–student interaction can also be moderated by the situation or context in which students are placed (Brophy & Evertson, 1978). Research in relation to context moderators is not abundant within the teacher expectancy field.

Transitional situations A meta-analysis completed by Raudenbush (1984) showed that the strongest TEEs tended to take place in the first, second and seventh grades. Larger effects of teacher expactancies have also been reported for adult trainees in a military programme (Eden & Shani, 1982). It seemed that these findings denied a moderating function of age, but they suggested moderation effects of situational factors (Jussim, Smith, Madon, & Palumbo, 1998). People, even adults, may be more vulnerable to self-fulfilling effects of interpersonal expectancy when they were transferring to new and unfamiliar situations (Weinstein & McKown, 1998). When people engage in major transitions, they may have unclear and weakened self-perceptions, which may increase the likelihood of expectancy effects (Jussim et al., 1998). Results from other findings also consistently show that when students are in transition phases, such as entering a new school level, they are more likely to behave in ways that confirm teacher expectations (Jussim, 1986; Swann & Ely, 1984; Li, 2014).

Ability grouping Grouping students refers to segregating students into different groups or classes according to their abilities. Grouping, in the eyes of students and teachers, represents institutional justification for believing that students are different in IQ or academic potential (Jussim et al., 1998). Thus grouping may lead to more rigid teacher expectations. Also, compared with students who are not grouped, students in ability groups appear to be more susceptible to labelling effects, which are more likely to provoke self-fulfilling prophecy effects or perceptual biases of teacher expectations (Eccles & Wigfield, 1985; Hall & Merkel, 1985; Jussim, 1986, 1990; Palardy, 1969). Self-fulfilling effects of teacher expectations have been found to be strongest among students in the low ability groups when teachers use within-class grouping (A. E. Smith et al., 1998). Poor quality instruction (Jussim et al., 1998), reduced teacher effort (Evertson, 1982) and limited learning opportunities (Slavin, 1993) for students in low-ability groups may restrain student academic gains considerably. Some studies (e.g., Kelly & Carbonaro, 2012; Weinstein, 2002) have also discussed TEEs on students who are placed in higher groups. Teachers may hold higher expectations for students in higher groups, and placement in higher ability groups may provide students with increased learning opportunities and lead to greater academic gains over time. In addition, it has been argued that TEEs may be stronger for intact groups than for individuals in the classroom (Brophy, 1983; Jussim & Fleming, 1996; Rubie-Davies, 2008a). Group-level expectancy effects are anticipated to be more powerful because students may function as a member of a group more than an individual, a false belief about a group may be more credible and more difficult to disconfirm, and teachers spend more time addressing the classes or ÂŠ 2016 The author and IJLTER.ORG. All rights reserved.

groups as a whole than addressing their students individually (A. E. Smith et al., 1998).

Class/group size TEEs may be more likely to happen in classrooms or groups with larger numbers of students than in smaller classrooms or groups. This is because teachers in larger classrooms or groups are busier and more occupied, and therefore more susceptible to biases or rigid expectations (Brophy, 1983; M. L. Smith, 1980). On the other hand, teachers in smaller classrooms or groups show less differential attitudes to students and even put in more effort to compensate for low expectation students (Weinstein, 1976). In addition, with limited resources in larger classrooms or groups, such as computers, laboratories, and athletic facilities, teachers may find it more difficult to manage instructional practice, and thus be more subject to perceptual biases and self-fulfilling expectancy effects (Rosenthal & Rubin, 1971).

Nature of the content being taught It has been proposed that with tasks of familiar content and predictable difficulty, teachers are likely to form accurate expectations and therefore expectancy effects are less probable (Brophy, 1983). One empirical study has found that larger TEEs take place in relation to student reading achievement than for mathematics achievement (M. L. Smith, 1980), which may be due to the differences in instructional practice used in teaching reading and mathematics. For example, reading may be taught in small groups while mathematics is often taught to the class as a whole (Cooper, 1985; Good & Brophy, 2009). Rubie-Davies (2008a) reported that class-level TEEs varied across curriculum areas, being more salient in reading than in physical skills. Sorhagen’s longitudinal study (2013) also found varying TEEs across academic subjects. Teachers’ false expectations in mathematics and language abilities ―seemed to have a more meaningful effect on students from lower income families‖ (p. 475) than the effect in students’ reading abilities. Another moderator related to the subject is when new content is being introduced. The relationship between teachers’ expectations and student outcomes may be strengthened when students are highly reliant on teachers as limited sources of the new content (Braun, 1976; West & Anderson, 1976). Li’s study (2014) argued that TEEs in foreign language classrooms were pronounced because teachers and classrooms were the major sources of learning opportunities. Additionally, if subject matter is taught through peer-tutoring or self-pacing to a larger degree than through teacher delivery, TEEs probably would be reduced (Cooper, 1985).

The review showed that individual differences in teacher, students and contexts may strengthen or weaken expectancy effects to a significant degree. That is to say, TEEs could possibly be modified by shaping and altering teachers’ and students’ beliefs and behaviours and some contextual factors. More importance should be attached to the teacher’ role in generating expectancy effects, because research highlighting the ―teacher‖ factor has been comparatively scarce and has become the latest focus in the related field. Apart from what has been reviewed above, some studies have also shed lights on the teacher’s role in producing TEEs. For example, a study in Singapore (Ker, 2016) reported that students’ achievement in mathematics was more likely to vary in line with their teachers’ beliefs and expectations. Another investigation into Mexican American students (Wentzel, Russell, & Baker, 2016) found that teacher variables were significantly predicting student academic outcomes. Professional development programmes for pre-service and in-service teachers could be planned to enhance teachers’ expectations and modify their behaviours in instructing and interacting with their students. However, caution should be taken because teacher expectations are not isolated but interrelated with other teacher variables for example teacher beliefs and self-efficacy. Teachers may modify their beliefs and behaviours to build a more positive instructional and socioemotional environment and more and better opportunities for student learning, which may lead to substantial academic gains by their students. Hence, how to distinguish different types of teachers seems worthwhile. Teachers’ expectations may be functions of some characteristics, such as some demographic features, and pedagogical beliefs and self-efficacy; and these could be identified by large-scale empirical studies in the future. In addition, very little research has been done to investigate the contextual moderators of teacher expectation effect, compared with studies of teachers and students in the mechanism. Contextual factors should not be neglected and merit more attention. For example, the impact of ―curriculum area‖ has not been fully explored in the expectancy field. It can be anticipated that TEEs would be more salient in some classrooms because of the features of particular subjects. What is worth noting is the institutional settings. For instance, TEEs have been seldom studied in tertiary institutions. In future research, to enhance student academic gains and to achieve educational equality, there is a need to explore closely all variables for promoting positive expectancy effects and eliminating negative expectation effects.

Acknowledgement: This article was supported by the Southwest University Teaching Reform Fund [2015JY062]

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International Journal of Learning, Teaching and Educational Research

Vol. 15, No. 2, pp. 94-105, February 2016

Principles and Practices of ESP Course Design—A Case Study of a University of Science and Technology Chin-Ling Lee National Taichung University of Science and Technology

Taiwan, R.O.C.

Abstract. The study is aimed to investigate the learners’ perspectives of perceived needs on their ESP (English for Specific Purposes) course at a university of technology. Two groups of 257 students of varying proficiency levels participated in the study, including English majors and non-English majors. A learner’s needs analysis questionnaire was administered to collect data from the subjects using the survey method. The data was analyzed via the SPSS software package for window. It was concluded that the extent of ESP needs perception held by the students was very high, about 80% of students thought ESP courses are useful and helpful for the future job. Plus, the English skill needed most was writing skill and students with the higher English proficiency held significant difference from the lower on interest in English learning. Keywords: needs analysis; English for specific purposes (ESP); international business

Introduction The international business world is a complicated field with a number of exotic cultures which makes the teaching approach on international trade and business transactions more challenging. Given the concept of the global economy, it is inevitable to provide students with a comprehensive but professional English relevant courses in order to meet the needs of international business operation. As long as presenting clear objectives and understanding what students expect

of, a feasible and practical English for Specific Purposes (ESP) course design would be carried out for a successful and particular business English teaching. Research Purposes ESP courses are widely provided in higher education in Taiwan. The most common ones are business English, technical English, or major-based courses for specific purposes. It should be appropriate for the purposes to share the newest developments and advances in knowledge and practice of international business to cope with the global environment. It is for the purpose of sharing the teaching experience and exchanging relevant information on business English course design, the study is focused on a case study on business English courses, in term of investigating the learnersâ&#x20AC;&#x2122; needs and requirements to help them adjust to their further academic study or future business career. In addition to a wide review of literature on ESP, this paper is aimed to present fundamental support for EFL instructors developing business English courses. Educational system in Taiwan provides students with more than ten years of intensive English training, in terms of language listening, speaking, reading and writing. Moreover, the government has strived for elevating the English abilities of their people. Nevertheless, a big discrepancy has still remained relatively high between general English level required for university EAP and the requirements of ESP for real workplaces. Plus, the majority of teachers are not native speakers of English and the fields of their expertise are general English teaching rather than occupational English used in the world of international businesses. Worst of all, materials provided are not authentic content of the workplace texts. These materials might fail to integrate the academic English into the required specific English tasks needed in the international business world. Therefore, the preliminary step is to examine current business courses in order to find out the demerits and restrictions. Simply put, it would be the first step to implement a simple needs assessment for the ESP course design. Questions of Research Research questions are accordingly illustrated on the basis of the purposes of the present study as follows: 1. What English language skills do the students perceive that they will need the most in their future work? 2. Do the perceived needs of ESP differ among students by gender?

3. Do the perceived needs of ESP differ between English major and Non-English major students? 4. Do the perceived needs of ESP differ among the variety of the students’ English proficiency levels? 5. Do the perceived needs of ESP differ among expected future jobs of the students? Definition of Terms 1. English for specific purposes (ESP): The foundation of ESP is an approach to ELT to meet learner need and it is “an approach to language teaching in which all decisions as to content and method are based on the learner’s reason for learning (Hutchinson & Waters, 2001).” 2. Needs analysis: A needs analysis of ESP course is usually referring to not only an indispensable process of clustering information on the requirement of the students, but also a basis of a curriculum development for general English courses or English for Specific Purposes (ESP) to satisfy the needs of a particular group of students (Iwaii et al., 1999). In the study, the analysis of needs is an approach on processing statistically descriptive data collected from the students’ responses to a questionnaire of needs analysis adopted from Balint (2010).

Literature Review This literature review consists of three sections: one to define the needs analysis, the other to indicate the needs analysis in ESP curriculum development, and another to explore the current state of ESP course design in Taiwan. What is ESP? As for the more focus on the question “What is ESP?” the greater details might come out to explain its discrepancy from English Language Teaching (ELT), either EFL or ESL. Although people think ESP is all but essentially language-centered approaches for the particular learners to gear up with particular or professional knowledge of specific subjects through the process of English learning, the learning processes of ESP is not much different from those of general English. Except for the various content of learning, ESP could as well be used in the learning of any kind of English. Therefore, “ESP must be seen as an approach not as a product” as what Hutchinson and Waters (2001) indicate, which illustrates that ESP is a learner-centered approach to English learning.

Origins and Development of ESP The emergence of ESP was not imminent until in the late 1960s. Underlying its theoretical and practical focuses, “it was particularly associated with notion of a special language and with important sub-field of English for science and technology (Far, 2008).” Later on, the view of communicative function was applied to ESP and the importance of needs analysis was brought into the focus of the perspectives on learners’ needs for English learning and language skills. The fundamental of needs analysis for ESP is first to define the situation or premises in which the learners will use English and practice their profession, and then the relevant instruction is aligned accordingly. Consequently, teachers of ESP courses provide authentic and specific language in their students’ needs to succeed in future career. Needs analysis The overview of needs analysis in language teaching has depicted its history, theoretical foundation, and approaches. Needs analysis is also regarded as demand or requirement needs, which has become a necessary and important stage of course design for either general English course or English for Specific Purposes (ESP) course(West, 1994). Learner’s needs has been the principle of the curriculum development of ESP. As defined by Johns and Dudley-Evans (1991), it can be regarded as what field the learners will practice English in the future. Studies on learner needs focused on the “needs analysis” and “needs assessment,” including the survey about students’ backgrounds and goals, as well as interviewing the faculty (Johns, 1981; Howorwittz, 1986). The more learner needs are clear, the more the objectives are expressed and the ESP course easily becomes successful (Theeb, H., & Albakrawi, M. (2013). Since needs analysis has become a prerequisite and necessary condition, it is also expounded as a guidance of course design or an evaluation of the students’ existing perceptions of needs. Although experienced teachers may ask students directly to understand what they expect of the class in the very beginning, a well-aligned needs analysis involve just much more than that. Needs analysis can help teacher gather information to find out how much the students already know and what they still need to learn. Pourshahian et. al. (2012) concluded the results of previous studies and suggested the needs analysis should be to learn

what aspects of language the learners need to study, what degree they need to study and why the learners study language. Berwick (1989) stated the administration of needs analysis can help course designer realize the discrepancy between a current state of learnerâ&#x20AC;&#x2122;s language skills and a desired future state. Generally speaking, the previous studies on needs analysis usually focus on collecting data on the perspectives of learners' wants, needs and expectation in terms of attitudes, beliefs and viewpoints. Furthermore, detailed information about all contextual factors like learning materials, aids, and environment are included into a more comprehensive needs analysis (Boroujeni & Fard, 2013).

Method The present study investigated the perspectives and perception on the needs of ESP courses among students in a technological university. The information of the demographic part was as follows; 257 three-year students including 62 males and 195 females voluntarily participated in this study; 105 were English majors and 152 were non-English majors; their English proficiency level range was between elementary to advanced ones; 158 of the participants expected English related jobs as their future career, whereas 99 of them chose non-English related ones, including, and 62 males, 195 females. A Six-point Likert scales questionnaire by Balint (2010) was adopted to find out the needs of Taiwanese college students from the language point of view. The questionnaire was distributed to 257 respondents. The questionnaire consisted of two parts; one was the demographic part for personal information and the other was questionnaire items for the perceived language skill needs. The origin English version was translated into Chinese to prevent students from misunderstanding the question items. A pilot test with 52 second-year students was implemented to check for each item wording and the construction of the questionnaire. The formal questionnaire consisted of 35 five-point Liker scale items. Both item analysis and reliability were processed to support the construct validity of research instrument. The Cronbachâ&#x20AC;&#x2122;s alpha reliability of the instrument was .92. The questionnaire was scrutinized by two English teachers to gain the content and face validity. The formal questionnaire was distributed to the students to collect the data. Descriptive, t-test and ANOVA statistic via SPSS statistic software package for

windows were used to analyze the collected data.

Results and Discussion The result of the analysis of first question was presented in Table 1. Most (50% or above) students were interested or very interested in learning English. Among the interest in learning English, item 6 and 8 had the much highest percentages, 83.3 and 85.2 respectively, which concluded that the students all believed in having good English proficiency would be of great help to their future career. The least frequency was item 4 indicating half of the participants did not expect to seek an English-related job after graduation. Moreover, among the ESP, EAP and general English courses, the students felt most interested in ESP instruction (78.2%) and considered ESP courses could be more useful for their future English needs. Table 1

Descriptive statistic for the category of “Interest in learning English”

Interest in Learning English %

From Usually To Always

1. I choose to attend this course because of the opportunity to take 2.

upper-division English-medium courses.

3. I have a goal to take elective courses taught in English in my 4 years of 4.

55.2

country while I am a university student.

7. I have a goal to get a job which requires English after graduating from 8.

55.1

university.

5. I am interested in doing a study abroad program in an English-speaking 6.

74.1

47.9

university.

9. Learning English is a challenge that I enjoy.

66.5

10. I want to learn English to be more educated.

83.3

11. I believe learning English is important to get a good job after graduating 85.2 from 12.

university.

13. If taking English courses in the ESP were optional, I would choose to take 14.

60.3

them.

15. I think English for specific purposes (ESP, or work-related English) 78.2 instruction 16.

is useful for my future English language needs.

17. I think English for academic purposes (EAP) instruction is useful for my 18.

future English language needs.

50.6

100

19. I think general English instruction (Everyday conversational English and 20.

75.8

travel English) is useful for my future English language needs.

21. Among the three types of English instruction, I would like to take the 22.

56.4

ESP/work-related English Table 2 presented findings regarding the importance of four English language skills which the students perceived. The mean scores of the perceived skills were 4.03, 4.27, 4.03, and 4.05 respectively regarding reading, listening, speaking, and writing. Listening skill was concerned to be the most important and needed skill to be geared up with, which might also show the lack of the studentsâ&#x20AC;&#x2122; English listening skills. Table 2 Descriptive statistic of mean scores of the perception on the importance of four English skills

Reading

Listening

Speaking

Writing

Mean

4.03

4.27

4.03

4.05

Std.

.647

.588

.682

.723

Table 3 illustrated findings for gender difference in perceived needs of four English skills. The importance and needs of listening was the most concerned sub-skill between male and female students (mean = 4.23 and 4.29 respectively). The result of the independent sample t-test showed no significant differences between males and females, which meant male and female students held similar viewpoints on the importance of each English skills. Table 3 Descriptive statistic of mean scores of four English skills by gender difference

Gender Male

Mean

Std.

Gender

3.99

.647

Female

Listening 4.23 Speaking Writing

Reading

Mean

Std.

4.04

.648

.682

Listening 4.29

.557

4.07

.723

Speaking

4.02

.670

3.99

.859

Writing

4.06

.676

Reading

In Table 4, there showed the mean scores of interest in English learning, reading, listening, speaking, and writing among different English proficiency level. As for interest in English learning, students at higher proficiency level showed higher mean score, indicating elementary and advanced levels at 3.67 and 4.18 respectively.

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Moreover, the perceived needs or importance of four language skills showed the highest each at the advanced level and the lowest at the elementary level. Students at elementary level held highest needs on listening skill (M= 4.19) and lowest on speaking (M= 3.87), at intermediate level (M=4.33 for listening, M=4.08 for reading, at the intermediate-high level (M= 4.39 for listening, M=4.06 for writing), and at the advanced level (M=4.85 for listening, M= 4.50 for reading) Table 4 Descriptive statistic of means by different English proficiency level

Proficiency

N Interest English

in Readin g

Listening Speaking Writing

Elementary

119

3.67

3.94

4.19

3.87

3.93

Intermediate

119

3.97

4.08

4.33

4.15

4.13

Intermediate-

4.12

4.13

4.39

4.13

4.06

Advanced

4.18

4.50

4.85

4.57

4.80

Total

257

3.84

4.03

4.27

4.03

4.05

high

General Linear Model was employed to examine whether or not there were significant differences on four language skills needs by studentsâ&#x20AC;&#x2122; different English proficiency levels. The statistics analysis of the multivariate test showed significant with the Pillaiâ&#x20AC;&#x2122;s Trace value at .131 (F = 2.30, p= .03 < .05) for the unequal groups. After processing the post hoc test, the findings showed that students at elementary level held significant difference to intermediate and intermediate-high levels on interest in English learning. According to Table 4, the results indicated that students at higher English proficiency level held higher interest in English learning. Moreover, students at elementary level held significant difference to intermediate levels on English speaking needs. According to Table 4, the result stated that students at higher English proficiency level held much more needs on English speaking skill. Table 5 The multiple comparison of different English proficiency level by Scheffe test

Dependent Variable Interest

(I) Level inElementary

Mean Std. Error Difference (I-J)

Sig.

-.2983

.000

(J) Level Intermediate

6.517E-02

102

English Intermediate-high -.4503

.1420

.020

Advanced

-.5146

.2295

.173

.2983

6.517E-02

.000

Intermediate-high -.1520

.1420

.766

Advanced

-.2162

.2295

.828

.4503

.1420

.020

Intermediate

.1520

.1420

.766

Advanced

-6.4286E-02 .2619

.996

Elementary

.5146

.2295

.173

Intermediate

.2162

.2295

.828

Intermediate-high 6.429E-02

.2619

.996

Intermediate

8.334E-02

.403

Intermediate-high -.1912

.1816

.775

Advanced

-.5602

.2935

.305

.1429

8.334E-02

.403

Intermediate Elementary

Intermediate- Elementary high

Advanced

Reading needs Elementary

Intermediate Elementary

-.1429

Intermediate-high -4.8319E-02 .1816

.995

Advanced

-.4174

.2935

.569

.1912

.1816

.775

Intermediate

4.832E-02

.1816

.995

Advanced

-.3690

.3349

.750

Elementary

.5602

.2935

.305

Intermediate

.4174

.2935

.569

Intermediate-high .3690

.3349

.750

Intermediate

7.542E-02

.367

Intermediate-high -.1975

.1644

.696

Advanced

-.6518

.2656

.113

.1345

7.542E-02

.367

Intermediate- Elementary high

Advanced

Listening needs Elementary

Intermediate Elementary

-.1345

Intermediate-high -6.3025E-02 .1644

.986

Advanced

-.5173

.2656

.287

.1975

.1644

.696

Intermediate

6.303E-02

.1644

.986

Advanced

-.4543

.3031

.524

Elementary

.6518

.2656

.113

Intermediate- Elementary high

Advanced

103

Intermediate Speaking needs Elementary

.5173

.2656

.287

Intermediate-high .4543

.3031

.524

Intermediate

8.663E-02

.020

Intermediate-high -.2587

.1888

.599

Advanced

-.6975

.3050

.159

.2737

8.663E-02

.020

Intermediate-high 1.501E-02

.1888

1.000

Advanced

-.4238

.3050

.588

.2587

.1888

.599

Intermediate Elementary

Intermediate- Elementary

-.2737

high

Advanced

Writing needs Elementary

Intermediate

-1.5006E-02 .1888

1.000

Advanced

-.4388

.3481

.662

Elementary

.6975

.3050

.159

Intermediate

.4238

.3050

.588

Intermediate-high .4388

.3481

.662

Intermediate

9.243E-02

.199

Intermediate-high -.1277

.2014

.940

Advanced

-.8706

.3255

.070

.2000

9.243E-02

.199

Intermediate-high 7.227E-02

.2014

.988

Advanced

-.6706

.3255

.239

.1277

.2014

.940

Intermediate

-7.2269E-02 .2014

.988

Advanced

-.7429

.3715

.264

Elementary

.8706

.3255

.070

Intermediate

.6706

.3255

.239

Intermediate-high .7429

.3715

.264

Intermediate Elementary

Intermediate- Elementary

-.2000

high

Advanced

The mean difference is significant at the .05 level.

Furthermore, Table 6 illustrated the correlations among different perceived English skill needs. There showed significant correlations among different variables at high level above .56 to .69, which presented there were close relationship between different English skill and students perceived each individual skill was important for their English learning.

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Table 6 Correlations of the perceived skill needs

Interest inReading Listening Speaking Writing English Interest inPearson English

1.000

.577

.568

.654

.553

.000

Correlation Sig. (2-tailed) .

.000

257

Reading

Pearson

.577

1.000

.692

.616

.566

needs

Correlation Sig. (2-tailed) .000

.000

257

.568

.692

1.000

.683

.647

Sig. (2-tailed) .000

.000

257

Speaking

Pearson

.654

.616

.683

1.000

.676

needs

Correlation Sig. (2-tailed) .000

.000

257

Writing

Pearson

.553

.566

.647

.676

1.000

needs

Correlation Sig. (2-tailed) .000

.000

257

Listening Pearson needs

Correlation

257

Correlation is significant at the 0.01 level (2-tailed).

Conclusions The present study was aimed to measure the perceived needs of four English skills and interest in English learning from the students of a technological university. The major findings depicted the needs perception held by the students were at very high level, indicating students realized that four English skills were all important and needed to be much improved to help with employment advantage or the future job performance. Still, more than half of the students did not expect to obtain English-related jobs after graduation, which may indicate their view of current situation of traditional industries in Taiwan. And students at higher proficiency level held more interest in English learning than those at lower level, which showed the importance of motivation and the

105

inspiration of learning achievement. Last but not least important, among four language skill needs, listening skill was the most need one, followed by writing skill, and these findings could be presented as a useful suggestion to English teachers that students think and perceive that the productive skills need to be much more improved.

References Balint, M. (2010). Assessing studentsâ&#x20AC;&#x2122; perceived language needs in a needs analysis. Retrieved

November

2012

from

http://www.paaljapan.

org/resources/proceedings/ PAAL9/pdf/BalintMartin.pdf. Benesch, S. (1996). Needs analysis and curriculum development in EAP: An example of a critical approach. TESOL Quarterly, 30(4), 723-737. Berwick, R. (1989). Needs assessment in language programming: From theory to practice. In R. K. Johnson (Ed), The second language curriculum, 48-62. Cambridge: Cambridge University Press. Boroujeni, S. A., & Fard, F. M. (2013). A needs analysis of English for specific purposes (ESP) course for adoption of communicative language teaching. International Journal of Humanities and Social Science Invention, 2(6), 35-44. Far, M. M. (2008). On the relationship between ESP & EGP: A general perspective. English for Specific Purposes World, 1(17), 1-11. Hutchinson, T., & Waters, A. (2001). English for specific purposes (16the Ed). UK: Cambridge University Press. Iwai, T. Kondo, K., Limm, S. J. D., Ray, E. G., Shimizu, H., and Brown, J. D. (1999). Japanese

language

needs

analysis.

Available

http://www.nflrc.hawaii.edu/Networks/NW13/NW13.pdf. Pourshahian, B., Gholami, R., Vaseghi, R., & Kalajahi, S. A. (2012). Needs of an ESL context: A case study of Iranian graduate students. World Applied Sciences Journal, 17(7), 870-873. Theeb, H., & Albakrawi, M. (2013). Needs analysis of the English language secondary hotel students in Jordan. International Journal of English Language Teaching, 1(1), 13-23. West, R. (1994). Needs analysis in language teaching. Language Teaching, 27(1), 1-19.

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International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp. 106-116, February 2016

Escalating Ability to Write Papers: To Make Use of Direct Instruction Ismail Marzuki Faculty of Teacher Training and Education, University of Muhammadiyah Gresik, Jl. Sumatera 101 GKB, Randu Agung, Gresik, Indonesia. E-mail ilmailmarzuki@yahoo.co.id Abstract. The purpose of this study is to determine whether using a model of direct instruction can improve writing skills on papers for students of Primary School Teacher of Education (PGSD) at University of Muhammadiyah Gresik (UMG). This research is a classroom action research (CAR) with the subjecst of class "A" of the first semester. The research also involved two fellow lectures as observers. This research was performed in three cycles by focusing on students' ability to write the cover, introduction, background, systematic procedures of writings, and a list of references, where all these things are indispensable in preparing a good paper. The results show that the students have been able to write representative papers indicated by improving the quality of papers that have been collected. It can be concluded that the model of direct instruction can improve students' writing ability to compose papers. Keywords: Writing Papers, Direct Instruction

Introduction A Language skill plays an important role in human life, because all areas of life need it. Based on the index survey of language skills (especially reading) of the population of Indonesia is in position of 39 in the world rank. This reality is an irony given the importance of th language skills for communication in the world. Lack of language skills, according to Muslim (2011), is due to many factors, including: curriculum, teachers, students, infrastructure, and the government as policy maker. Another problem worsens this condition is that the common practices of conventional learning and teacher-centered (not student centered), too many numbers of students in a class, and too many administrative tasks of teachers. Therefore, we need innovations to go out of this problem by innovations in learning. To learn the language cannot be separated from the four aspects of language skills: listening, speaking, reading, and writing. Writing is one of the four language skills in which it essentially is an attempt to convey messages, ideas, and feelings to others through graphic symbols or texts

107

(Mulyati, 2002). Writing is also consiere an effective form of communication besides oral communication. Language learning goals are to improve the ability of learners to be able to communicate well, both orally and in writing (Depdiknas, 2006). At higher education level, aspects of speaking and writing are important because both are needed to support learning other subjects. Aspects of speaking are needed when presentations, discussions, submission of ideas, questions and answers, etc., while writing aspects are needed during the composition of writing papers, book reports, resumes, manufacture thesis, and even a dissertation. Writing has a strategic and significance role for the students, as a means of publication in the academic world. Therefore, writing needs to be trained, habituated, and familiarized when someone studying at college. Writing is not easy, because many students have difficulty when given the task to make writing such papers and thesis. Frequently, someone is failing to study in college because he or she is not able to finish thesis. In particular, students' paper focuses more on products' writing or articles of researchs and non researchs. According to Heuboeck (2009), domain and level of significance of text are divided into three groups: global, macro and micro. Global domain consists of text loads that describe the relationship between pragmatic (global coherence) and logical (functions). Domain of macros illustrates the semantic linkage (propositions), while the micro domain consists of a linkage between units and syntagmatics (textual). Therefore, the understanding of ways and structures of academic papers must meet the good rules particularly when making the introduction. To write the introduction becomes a very important part because readers will easily capture the contents of the paper if the preliminary information is able to describe the importance of the reasons to be put forward by the authors in it. Thus there are some important things to consider (Swales: 2004) they are:: 1. To express current knowledges in the areas being studied. 2. To explain the summary of previous findings and provide a broader context and background of the importance of the focus. 3. To provide an overview of writing plan and show the gap on the focus by presenting the question. 4. To introduce the objectives and designs of the plan. Furthermore, according to Agrawall (2015), to develop introduction in the paper, exactly there is a difference between native authors and non natives in which the writers of non-native usually are not interested in using claiming a nich, but they tend to use establishing a nich, as well as the use of gap, the nonnative writers are not easy to use in writing a paper. To create the adequate introduction it needs review of theories related to the focus or the main purpose of the article. Thus the study of theory is essential to support the quality of the article that is being developed. Onwuegbuzie, Leech, and Collins (2012) explains that to support the review theory in a paper needs efficient ways because the purposes of the theoretical review itself are as follows: 1. Clarify the research problems being studied as optimal as possible. 2. Provide supporting relevant resources. 3. Demonstrate reasons to use related references.

108

4. Clarify the terms used in the keywords. 5. Indicate the main sources used and summarize them well. Many students' writing are mostly not quite readable and complicated because some terms are usually difficult to understand and many times jumping due to unclear wordings. To overcome these problems require serious and structured efforts so that similar bad conditions will not occur again. Because the researchers intend to act in class 'A' on the Elementary School Teacher of Education Program, University of Muhammadiyah Gresik. At this department, subject of writing paper is given for three semesters, namely semester 1, 2 and 3. This course contains 9 credits which becomes the core course of science educationa. The learning competencies include four types, namely; to understand the general guidelines of papers; to write introduction according to the standardized rules; to review related literature; and to report findings and conclusion properly. Based on the preliminary observations of the writing problems of students, on average, their capabilities are still not good. There are nine out of ten papers that have many errors especially on the background development which is not original yet. Similarly, when writing the formulation of the problem, the purpose is not stated clearly so that the information is sometimes not related at all with the focus to be investigated on title. Writing error rate even reached 85%, including the systematics, spelling, and citation. This errors must be addressed, because it can adversely impact when the students make a paper, a research proposal, even thesis. Therefore, a team of lecturers plan to hold actions in the classroom by using the directinstruction model. The rationales of the use of this model are: 1. This model is suitable for developing performance-oriented capabilities, one of which is the ability to write; 2. This is suitable for the skills and abilities related to task-oriented; 3. This is suitable to help learn the basic knowledge or procedural skills ; 4. This model allows the students to master in a short time; 5. Writing is a basik skill that should be structured and performed gradually (Nur, 2011:27). RĂźĂźtmann & Keeper (2011) states that there are two general teaching strategies that lead to learning outcomes, namely direct and indirect instruction instruction. Direct instruction is usually used to equip students to understand the facts, rules, order, and so leading to pshycomotor domain. While indirect instruction is a teaching strategy that helps students understand abstract concepts or things that require a high complexity. However, in the implementation of the class, usually two types of strategies can be combined in the form of problem solving, cooperative working, or case studies. Furthermore, Moore (2012) explains that the direct Instruction has five steps, namely orientation, presentation, structured practice, guided practice, and independence practice. This study, therefore, uses a direct instruction of teaching strategies to improve students' ability to develop the ability to write paper.

109

Research Method This research is a classroom action research which is conducted in the classroom of "Morning" first semester of the department of Elementary School Teacher at University of Muhammadiyah Gresik with the subjects of 45 students of class "A". The research also involved two fellows of faculty members and observers. Specific Learning Outcome (CPK) which is the target of the research is the students are able to write according to the standard rules of writing papers. Designs of this study are: Reflection at the beginning → planning actions 1 → implementation of measures 1 and observation → reflection and evaluation 1 → plan of action 2 → implementation of actions 2 and observation → reflection and evaluation 2 → plan of actions 3 → implementation of actions 3 and observation → reflection and evaluation 3. The procedures of the research are: planning action, implementation of action of learning, plan of recording, and analysis of data. The analysis model is the strategy developed by Miles and Huberman, whose activities include 3 things done simultaneously: (1) data reduction, (2) presentation of data, and (3) conclusion / verification. After the data were analyzed, the results were used as reflections conducted at each end of the cycle. In addition to discussing the shortcomings of action, reflection is also addressed at all stages of the research process. Results of reflection will be used as input for improvement in the preparation of an action plan in the next cycle. The data used is the result of observation and reflection of the impact of action. Results of observation are all recorded related to the attitude and student response to the actions of researchers. The action impact is a skill that is achieved by the students as a result of actions taken by researchers. Results are included in the group impact studying of this action. Data from the study was then assessed and classified based on the established criteria. Data were obtained through two ways: through observation in the classroom and by measuring student learning outcomes.

Findings and Discussion This study was conducted on 23 November to 7 December 2015. The results of the research are as follows: Cycle 1

Skills to be achieved in this cycle is the students can write the cover, write the preface, write background, and write formulation of the problem. Action cycle 1 was conducted on Monday, November 23, 2015 at 12:30 to 14:30 pm on the subject of writing paper. There are three categories of assessment standard: good, sufficient, and fair. Description of the assessment standards can be seen in the following table: Skills

To write Cover

Table 4.1. The category of assessment in cycle 1 Assessment Good Sufficent Fair (91-100) (81-90) (71-80) The writing is The writing is The writing is complete, appropriate, complete, complete, but not and proporsional. appropriate, but not appropriate, and

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To write aknowle dgement

The writing includes gratitude, title, objectives, thanks, expecting input from reader, and the name of the author-town

To write The writing mentions backgrou the urgency of the nd theme, there is field data and mentions the impacts if the problem is not examined / investigated To write problem statemen ts

Formulation of the problem is according to the theme, the meaning of the phrase is clear, and the statement is right.

proporsional Same with the good category, but does not mention the purpose of writing and acknowledgments,

not proporsional Same with the good category but does not mention the purpose of writing, thanks, and do not ask for input. Same with the good Same with the category but does good category not mention the field but does not data. mention field data as a the impacts if the problem is not studied. Formulation of the Formulation of problem is the problem is according to the according to the theme, the meaning theme, the of the phrase is clear, meaning of the but the writing is sentence is less less precise. clear and less precise.

Student results are seen from the quality of their writing products. Data shows that in writing cover there are 67% of the students get a good value, 33% sufficient, and no student whose value is fair. Writing the aknowledgement, 73% students are good, 25% adequate, and 2% fair. Writing background, 73% students are good, 18% sufficient and 9% lfair. Writing formulation of the problem 18% of students are good, 22% adequate, and 60% fair. To facilitate a comprehensive analysis, the data is presented in graphical form as follows:

Graph 4.1. Learning outcome of cycle 1 80 60

Good

Middle

Low

0 Design Cover

Writing Writing Backround Writing Statement Acknowledgment of the Study of Problem

The graph above can be described as follows: 1. Most of the students have been able to write the cover, write acknowledgement, and write the background well. 2. Most of the students are sufficient for all three of their above mastery. 3. Most of the students have not been able to write good formulation of the problem.

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Results of the observational record show that: 1) the classroom atmosphere is relatively ordered although there is little noise; 2) students make notes when researchers present; 3) When the researchers give the students feedback they are not motivated; 4) researchers are in rush during presentations and demonstrations; 5) researchers are in a hurry while giving a guided exercise; 6) targets of students skills that must be mastered are too much; 7) the potentials of students are diverse; 8) there are still students that are difficult to focus after ice breaker; 9) some students are confused and difficult at the moment of guided exercises; 10) one student got impaired vision. After considering the observational record and after associating it with learning outcomes that the less optimal of student learning targets, especially the ability to write formulation of the problem, are caused by: 1. targeted skills to be mastered are too many, while time is limited. 2.The potential of students is diverse, so it takes different approach; 3. Researchers are in a rush when delivering presentations and demonstrations, causing the student does not understand; 4. Motivation of student learning is not optimal; 5. The way the students learn manytimes is not appropriate; 6. Ice breaker causes some students not be able to focus, so it needs some breaks until they are really ready. Based on the above descriptions it is suggested that: 1) When presentation it should not be in a hurry; 2) There should be sufficient time at each stage of learning; 3) To condition the students after the ice breaker to have better preparation; 4) Modify the guided exercises so that the result is optimal; 5) To repeat the background material and formulate the problem in cycle two. Cycle 2

The material of cycle 2 is writing background and writing the problem formulation. This material has actually been in cycle 1, but because the results are not satisfactory and many students who have not completed are decided to repeat cycle 2. This cycle was held on monday, November 30, 2015 at 12:30 to 14:30. Standard assessment is the same as in the first cycle with three categories: good, sufficient, and fair or low. Description of the assessment standard can be seen in table 4.2. Table 4.2.The category of assessment in cycle 2 Skills

To write backgroun d

Good (91-100) The writing mentions the urgency of the theme, no field data and mentions the impacts if the problem is not examined /

Assessment category Sufficient Fair (81-90) (71-80) The writing is The writing is same same with the with the good good category category but does but does not not mention the field mention the field data and the impacts data. if the problem is not studied.

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To write problem statement

investigated Formulation of the problem is according to the theme, the meaning of the sentence is clear and precise

Formulation of the problem is according to the theme, the meaning of the phrase is clear, but the formulation is less precise.

Formulation of the problem is according to the theme, the meaning of the sentence is less clear and precise.

Data from the study shows that 84% of students get good grades, 11% adequate, and 5% fair for the writing background. Meanwhile writing formulation of the problem shows that 82% of students get good grades, 9% adequate, and 9% fair. To facilitate the analysis, the data above are presented in graphical form as follows

Graph 4.2. Learning outcome in cycle 2 100 80

Good

Middle

Low

20 0 Writing Backround Writing Statement of the Study of Problem

The graph above shows that over 80% of the students have been able to write background and formulation of the problem well which means they have been completed. Cycle 3 Skills to be achieved in this cycle are the student able to: 1) quote well; 2 write with correct systematics; 3) write a list of references properly. The actions of cycle 3 was held on Monday, December 7, 2015 at 12:30 to 14:30. This skill of assessment standards is grouped into three categories: good, sufficient, and fair. Description of the assessment standards can be seen in the following table:

Table 4.3 Assessment category in cycle 3 Skills Good (91-100)

Assessment category Sufficient (81-90)

Fair (71-80)

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Ability to quote

The writing of citations and punctuation are correct and the sentences flow well.

The writing of citations and punctuation are correct, but the sentence is less flowing properly.

The systemat ics of writing

The writing is coherent, structured, neat, straight, and spaced regularly. The writing the name of the author, year, title of the book, the town, and publisher is correct.

The writing is coherent, structured, but less neat and straight.

The writing ofcitations are correct, but the it is still wit wrong punctuation and the sentences are less flowing well. The writing is less coherent, sloppy, and less regularly spaced.

Writing the name of the author, year, title of the book, the town, and publisher is less precise

Writing the name of the author, year, title of the book, the town, and publisher is not appropriate.

Ability to write the list of reference

Based on data from study it is found that: 60% of students in citing are good, 40% sufficient, and no fair value. For systematics of writing 80% of students are good, 16% sufficient, and 4% fair. Meanwhile writing the list of reference, all the students get good value. The display of total learning outcomes of this cycle can be observed in the following graph: Graph 4.2. Learning outcome in cycle 3 100 80 Good

Middle

Low

20 0 Writing Backround Writing Statement of the Study of Problem

The graph above shows that: 1. Completeness of writing the list of reference is the highest of 100%; 2. The majority (80%) students have been able to write good systematics writing ; 3. The interval of citing skills between categories of good and sufficient is in small margin with 20%. Meanwhile, based on the observation in the classroom, the data shows that: 1. The classroom atmosphere is better than the second cycle: more calm and conducive;

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2. When researchers presenting the material and feedback three active student asked; 3. The time to have guided practice is quicker. Based on the data from cycle 1 to cycle 3 it can be stated that: 1. The student motivation to learn is an important role; 2. It needs necessary analysis and careful calculation in determining the learning targets associated with available time; 3. The need to learn proper way of sharing with students is crucial; 4. There should be proper arrangement between the students with learning resources; 5. The need for personal guidance is intense because of the potential of different students; 6. Repeated exercise and continuous guidance are to improve the skills of students. Results of this study, therefore, have been consistent with what has been done by previous researchs (Moore, 2012; RĂźĂźtmann & Kipper, 2011), especially Mart (2013) who also have tested the direct instruction in which this strategy has a positive impact not only on student writing skills but also the ability of oral communication. The successful use of direct instruction is also the case in the development of the ability of students' reading (Kamps, Greenwood, Wills, Veerkamp, & Kaufman, 2008; Crowe, Connor, & Petscher 2009; Stockard, 2010) where direct instruction in this regard has been given a boost to students to get a better reading scores so as to encourage the spirit of learning which is further improved. This study not only supports the improvement of reading skills of students but also even help improve math skills (Stockard: 2010). Thus the use of proven direct-instruction can be used to help increase students' ability both in terms of cognitive, psychomotor, and good critical thinking in reading, oral communication, even in writing academic papers.

Conclusion The conclusions can be made as follows: 1. Using the three cycles, teaching strategy using direct instruction has a positive effect on students' ability to write the cover, introduction, background, systematic of writing, and a list of references, where all the points are indispensable in preparing a good paper. The results show that the students have been able to write a paper representatively supported by improving the quality of paper that has been collected. 2. Thus, this research concludes that the model of direct teaching can improve students' writing ability Based on the results of the study, the researcher wants to make suggestions as follows:

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1. For students, it should be capable of increasing self-motivation to learn because motivation plays an important role. To set correctly all learning sources and practice many times to really succeed. 2. For lecturers / researchers, they should analyze carefully in determining the target of learning, sharing need to learn in proper ways to students and guiding them personally because they are with different potentials.

References Agrawall, J. (2015). The Analysis of Rhetorical Structures in English Research Article Introduction Written by Native and Non-native English Authors in the Field of Finance. Retrieved on January 28, 2016 from https://www.researchgate.net/publication/287975309 Crowe, E. C., Connor, C. M., & Petscher, Y. (2009). Examining the core: Relations among reading curricula, poverty, and fi rst through third grade reading achievement. Journal of School Psychology,47, 187-214. Depdiknas. (2006). Permendiknas No. 22 tahun 2006 tentang Standar Isi Mata Pelajaran Bahasa Indonesia SD - SMA. Heuboeck, A. (2009). Some Aspects of Coherence, Genre and Rhetorical Structure – and Their Integration in a Generic Model of Text. Language Studies Working Papers. Vol. 1, 35-45. Kamps, D., Abbott, M., Greenwood, C., Wills, H., Veerkamp, M., & Kaufman, J. (2008). Effects of smallgroup reading instruction and curriculum differences for students most at risk in kindergarten: Two-year results for secondary- and tertiary-level interventions. Journal of Learning Disabilities,41(2), 101-114. Kristianto, H. Cara membuat makalah yang baik dan benar. http:// hengki kristianto ateng.blogspot.com. diakses tanggal 4 Mei 2015. Mart, Cagri T. (2013). The Direct-Method: A Good Start to Teach Oral Language. International Journal of Academic Research in Business and Social Sciences November, Vol. 3, (11). Moore, David, W. (2012). Direct Instruction: Targeted Strategies for Student Success. Retrieved on January 16, 2016, from http://ngl.cengage.com/assets/downloads/inside_pro0000000029/a m_moore_direct_instr_seb21_0414a.pdf Mulyasa. (2010). Praktik Penelitian Tindakan Kelas. Bandung: Remaja Rosda Karya. Mulyati, Y. (2002). Pendidikan Bahasa dan sastra Indonesia di Kelas Tinggi. Jakarta: Universitas Terbuka. Onwuegbuzie, Anthony J., Leech , Nancy L.& Collins, Kathleen M. T. (2012). Qualitative Analysis Techniques for the Review of the Literature. The Qualitative Report 2012 Volume 17, Article 56, 1-28, http://www.nova.edu/ssss/QR/QR17/onwuegbuzie.pdf Prabowo. (2011). Metodologi Penelitian (Sains dan Pendidikan Sains). Surabaya: Unesa University Press. Rüütmann, T. & Kipper H. (2011). Teaching Strategies for Direct and Indirect Instruction in Teaching Engineering. 14th International Conference on Interactive Collaborative Learning (ICL2011) ̶. 21–23 September 2011, Piešťany, Slovakia, Retrieved from http://oaji.net/articles/2014/4571408435110.pdf.

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Stockard, J. (2010). Promoting reading achievement and countering the “Fourth-Grade Slump”: The impact of Direct Instruction on reading achievement in fi fth grade. Journal of Education for Students Placed at Risk, 15, 218-240. Stockard, J. (2010). Improving elementary level mathematics achievement in a large urban district: The effects of Direct Instruction in the Baltimore City Public School System. Journal of Direct Instruction, 10, 1-16. Swales, J. M., & Feak, C. B. (2004). Commentary for academic writing for graduate students: Essential tasks and skills (2nd ed.). Ann Arbor, MI: University of Michigan Press/ESL. Wibowo, W. (2011). Cara Cerdas Menulis Artikel Ilmiah. Jakarta: PT. Kompas Media Nusantara.Yulianto, Bambang. Dkk. 2009. Model Pembelajaran Inovatif Bahasa Indonesia. Surabaya: Unesa University Press.

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International Journal of Learning, Teaching and Educational Research Vol. 15, No. 2, pp, 117-133, February 2016

Students’ Attitudes and English Language Performance in Secondary Schools in Tanzania Gilman Jackson Nyamubi, Ph.D University of Iringa, Tanzania

Abstract. The study explored the role of attitudes in secondary school students’ performance in the English language. It explored how learning English was silhouetted by students’ interests and utilitarian attitudes to the language. The fieldwork covered six secondary schools in Morogoro Urban and Mvomero districts in Morogoro Region. Respondents were students and their teachers of English. Data were collected through questionnaire and an achievement test. It was found that students differed in terms of their mastery of English, scoring higher in the structure section, while composition was the most poorly scored section. In all, students, in both Form One and Form Four, had strong and positive attitudes to English. Specifically, while Form One students had more positive interest attitudes than their counterparts, Form Four students displayed more utilitarian attitudes to learning English, compared to Form One students. Students’ positive attitudes are in line with the current Government policy on the language of instruction in secondary schools. The paper ends by emphasising that students’ positive attitudes to English can be exploited to enhance the learning of the language. Keywords: Students’ language attitudes; English language learning; performance; secondary school; Tanzania

INTRODUCTION Tanzania is essentially a multilingual society. The country has about 150 ethnically-based languages (Muzale and Rugemarila, 2008), used by several communities especially in rural areas. For most Tanzanians, matters pertaining to customs, values, humour and cultural practices are often better communicated by the use of these ethnic languages (Rubagumya, 1993). Kiswahili is the national lingua franca, official language and the second language for about 80 percent of Tanzanians (Mapunda, 2013). Mapunda (ibid.) further observes that the exclusion of ethnically-based languages from being used in the education system in Tanzania makes the transition of non-Kiswahili speaking children from the home language in a primary school language

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difficult. Primary school education in all public schools is derived through the medium of Kiswahili. Pupils learn English as a subject. At the secondary school level, there is a switch of the language of communication in which English takes over as a medium of instruction (URT, 1995). At this change point, most Pupils from public primary schools experience a new language, that is English, which, according to Komba, et. al. (2012), it is unfamiliar for expressing concepts that students previously learned in Kiswahili. In this experience, most learners feel a hard and confusing task of expressing themselves when they are not competent in the language (Roy-Campbell and Qorro, 1997). This situation might have been a logical consequence of successive narrowing down the sphere of English language in the Tanzanian society between 1960’s and 1980’s. During that time, the language was restricted to classroom use, and was used to only communicate with foreigners (Rubagumya, 1999). English language has, at various levels of use, historically been changing its role and status. It was both the national and the official language throughout British rule in Tanganyika (1918-1961). According to Rubagumya (1999), this served the interests of the colonial administration, which needed to communicate with all locals in one language-Kiswahili, and with the metropolis and business community in English. In the 1960s, the political agenda for Tanzania was disengagement from neo-colonialism and the building of a self-reliant society (Rubagumya, ibid.). Currently English is needed in Tanzania in order to have regional and international relationships, as it facilitates communication, and this language is more vital in this era of globalisation of information, technology and commerce. English language is taught as a language in all public primary schools, from class three onwards. It is also used as the medium of instruction in the education system, starting from secondary school to tertiary level. At Forms Five and Six levels, English language is taught as one of the subjects in a given combination. Similarly, in universities, it is one of the courses offered. Tanzania follows an education system of 7-4-2-3+, that is, seven years of primary school, four years of ordinary level secondary school, two years of advanced level secondary school and three years or more of university education (URT, 1995). Although English is spoken by few people, it occupies a high status as it is the language of higher education, in the judiciary system, and in diplomatic circles (Schimied, 1986). The Education and Training Policy (1995) presents that the objectives of language teaching in secondary education are to promote the development of competency in linguistic ability and effective communication. These objectives indicate that English language is a very important school subject and medium of communication at both local and international levels. The English syllabus for forms I-IV targets at enabling students to communicate effectively with other speakers of English language both inside and outside the country and use their knowledge of English in furthering students’ own education (URT, 2010).

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It is therefore expected that, after the ordinary secondary school level of education, students will have acquired and developed the specified knowledge, attitudes and skills of that language, so as to cope with the English language demands at higher levels of education and in the world of work in general. The effective learning of a foreign or second language depends largely on the attitudes of individuals to the target language (Baker, 1992). Little is known on how attitudes Tanzanian secondary school students have on English as a foreign language, would determine their learning and performance in English language as a school subject.

Statement of the Problem Despite the fact that English is taught in Tanzanian schools from the primary school level, the majority of secondary school students are performing poorly in national examinations (Mkumbo, 2012). This poor performance may be explained by the fact that learning a foreign language effectively is associated with learners’ attitudes and the utilitarian need to learn it (Nyamubi, 2003). In this way, factors such as learners’ academic advancement or career aspirations in life may shape their attitudes towards and performance in the language. In this frame of reference, this study was formulated to sift how students’ attitudes to the English language explain their performance in the subject. The study explored the trend of students’ performance in English. The major research objectives are two: First, to examine how students’ attitudes to learning English correlate with their performance in the subject, the realisation of which was guided by these questions: What are secondary school students’ attitudes to learning English? How do these attitudes explain their performance in English language in class? Second, to explore the performance level of secondary school students in English, the data of which were guided by two questions: What is the performance level of secondary school students in English? How do students’ demographic variables, gender and class level, elucidate their performance in the English language? Attitudes are important aspects in the formation of national language policy. Baker (1992) affirms that no policy on language can be successful if it does not conform to the expressed needs and attitudes of language users in the community. Thus, it is anticipated that the findings of the study might shed some light on possible ways of encouraging socially desirable attitudes to learning the language. It is therefore hoped that this study will contribute to improving the teaching and learning of English language, and hence lead to better students’ performance.

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RELATED LITERATURE In this section, a review of literature is made. It provides a discussion of the main concepts of the study in order to discern the gap to be filled in by the present study.

Attitudes and Language Learning Different people have defined differently the concept of attitude. To begin with, Anold (2005) defines attitude as either mental readiness or implicit predispositions that exert some general or consistent influence on a fairly large class of evaluative responses, which are usually directed towards some objects, events or persons. Ewen (2003) on the other hand, defines attitude as a mental and neural state of readiness organised through experience, exerting a directive or dynamic influence upon the individual’s response to all objects and situations with which it is related. The common characteristic in these definitions is that attitudes entail evaluative predispositions to respond to social objects that interact with situational variables, thus guiding and directing the overt behaviour of an individual. The working definitions preferred in this study are Ajzen’s (2001), who defines an attitude as a disposition to respond favourably or unfavourably to an object, person or event, and Armitage and Conner’s (2001), who see that the role of attitudes is to help locate objects of thought, such as language, as being an object that is perceived to be favourable or unfavourable. These definitions are preferred because they link attitudes to measurement, that is, whether they are favourable or unfavourable in relation to an object, person or event. In this way, if an attitude of a person to an object such as language is known, it can be used in conjunction with situations and it can explain a person’s reaction to it. A survey of attitudes provides an indicator of current community thoughts, beliefs, preferences and desires (Garrett, 2010). Attitudes comprise beliefs about things that have some social significance. Such beliefs, for example, can be values that are attached to English by many Tanzanians that knowing the language is synonymous to being educated (Mapunda, 2013). It also provides social indicators of changing beliefs and the chance of success in language policy implementation. Attitudes and motivation differ in that while attitudes are learners’ feelings of approval or disapproval to learn the target language (Mapunda, 2013), motivation to learn language is an extent to which an individual strives to learn the target language because of a desire to learn the language and satisfaction experienced in the activity of learning (Ushida, 2005). In this, a motivated learner is eager to learn the language, expand efforts to learn it, and to sustain the learning activity. This encourages language retention, fluency, need for achievement and improved strategies to increase students’ language comprehension levels (Wilkinson, 2015). According to Ushida (2005), motivation mediates the relationship between language attitudes and language achievement. The current study, however, examined the role students’ language

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attitudes in their performance in English without including motivation as mediating factor between the two variables under study, because other studies have dealt with this (Gardner, 2000, Ushida, 2005). Language as a tool for socialisation and determinant of individual knowledge of the world is highly gendered in language use in school and society (Kidenyi and Getui, 2011). Gender as a social constructed concept shapes interpersonal relation and the way people perceive language, that is, their attitudes towards that language in its use as well as learners’ overall performance. It determines how female and male students feel about the language they learn (ibid.). In education, attitudes could be both an input and an output. A favourable attitude to language learning may be a vital input in language achievement. Baker (1992) found the following: First, attitudes have a positive correlation with success in learning a second language; and second, they facilitate learners’ motivation to learn the language in relation to goal attainment. Attitudes can also be an outcome. After a language-learning course, the teacher and learners may have favourable attitudes to the language learnt, if they expect to benefit from it. In this way, learners will strive to achieve highly in the expectation of doing well in examinations and mastering the language, which in turn facilitates better performance. Gardner (1985) argues that second language learners with positive attitudes towards the target language learn more effectively than those who do not have such positive attitudes. He explains that learners’ language attitudes predict students’ degree of success in terms of linguistic outcomes in learning the target language. In language learning, attitudes seem to be very important in predicting learners’ academic performance. The learner’s favourable attitude to the language she/he is learning would facilitate success in it. Tahaineh and Daana (2013) argue that personal beliefs about one’s capabilities and positive attitudes towards what one is learning positively influence learning. In this way, learners’ positive attitudes to the language they are learning could help them to master the language, leading to success in their performance at school and after school linguistic needs in real daily-life situations. However, little is known about the contribution of students’ attitudes to English to their performance at the secondary school level in Tanzania. The present study therefore was intended to address this issue.

METHODOLOGY This study was conducted in secondary schools in Morogoro Region, Tanzania. The area was randomly selected from other twenty-five Regions, in Tanzania Mainland. Two districts in Morogoro Region, Morogoro Urban and Mvomero, were selected, from which six secondary schools were randomly picked for the study.

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Morogoro, like other regions, catered for the education of the local people from both urban and rural areas around the country. Schools in the area had varying characteristics in terms of student composition, which were essential aspects that explained students’ attitudes towards English language learning in relation to their performance in the language. The population of this study included secondary school students and teachers in Mvomero and Morogoro Urban districts. Six secondary schools were selected, that is, three schools from urban and the other three from rural areas. Specifically, the target population included Forms One and Four students and their teachers of English. Form One students were involved in the study because they had just completed primary education where majority of them, particularly from public primary schools, had been learning all subjects, except English, in Kiswahili. Additionally, because the language of instruction in primary schools is Kiswahili, with exception of English medium primary schools, it was important to find out how the change to English as the language of instruction in secondary schools could explain students’ attitudes to the English language. Form Four students on the other hand were involved in the study because, at their level, the English language syllabus content for ordinary level was supposed to have been covered by the learners. Additionally, Form Four students would have more immediate needs for the language for higher studies or employment, and that would adequately gauge students’ attitudes to learn English. Teachers of English were involved in the study, as they were the important input in the teaching-learning process. Their views on students’ attitudes to learning English were considered important to the study. Teachers provided information that was useful for analysing and discussing the findings. The sample comprised 450 students, that is, 230 males and 220 females. Their ages ranged from 12 to 17 years. In the selected schools, all Forms One and Four students had an equal chance of being involved in the study. Thus, the sample was 276 and 174 for Forms One and Four, respectively. Again, the sample can be categorised as 280 students from urban secondary schools and 170 from rural schools. Permission to access schools in the study area was obtained from relevant authorities and institutions, and all participants agreed to participate in the study. The selection of teacher respondents who participated in the study from each school was through the purposive sampling technique, which was utilised to deliberately choose respondents in accordance with the data that was intended to be collected. Thus Forms One and Four teachers of English from each school were included in the study on the merit of their duties.

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Student respondents, on the other hand, were selected by randomly picking one stream in each Form in every school that had more than one stream. Since streaming in Tanzania’s secondary schools is not based on ability, it was reasoned that, whichever stream was picked, it would provide a fairly representative sample of all students in that level. In schools where there was only one stream, there was no choice but to pick that stream. The number of students in each stream ranged from 25 to 65. Two data collection instruments were used in this study. These were questionnaires and achievement tests. Questionnaires, which included attitudinal rating scales, were twofold: one for students and the other for teachers. The Students’ questionnaire was designed to elicit their personal data, and their attitude to the English language. The standardised instrument for measuring individual students’ attitudes towards a language they learn was adopted from Krashen (1981). However, these items were modified to suit the Tanzanian situation, and in particular, in the context of English language learning at the secondary school level. The instrument had 15 items for interest attitudes sub scale and 10 items for the utilitarian attitudes sub-scale. In each section, respondents were to respond by rating the appropriate reply. Responses were tapped in a four-point Likert type format, ranging from strongly agree (4) to strongly disagree (1). To ensure that high scores indicated higher or positive attitudes towards English, negatively worded items were reverse scored. Scores obtained were correlated with students’ performance. The teachers’ questionnaire asked them to provide information on the students’ attitudes to learn English language. The achievement tests in both Forms One and Four were administered to students so as to ascertain their performance in English. There were two tests; one for Form One and the other for Form Four. They were both curriculumbased as they covered the content as stipulated in the respective syllabi. Both tests consisted of three sections, comprehension, composition and structure or grammar. The whole achievement test was marked out of 100. The marking of both tests was based on a marking scheme. The tests were marked by the researcher and two independent teachers of English. The scores obtained in both tests measured students’ performance. The students’ questionnaire and the achievement tests were administered by the researcher with the help of the teachers of English in each school. Questionnaires were distributed to each respondent, and enough time was given to respond to the questionnaire. Respondents completed a questionnaire at their schools in the presence of a researcher. Assistance was provided, as needed, to help in reading and understanding the survey items. Achievement tests were administered to students a day after they had filled in the questionnaire. Time for the test in both classes was one hour, which was enough for respondents to complete all test questions. As for teachers, questionnaires were distributed to each respondent by the researcher. The time and day for collection were set.

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As regards validity and reliability of the instruments, the questionnaire was written in English and later translated into Kiswahili with assistance of a person fluent in both languages. This ensured consistency in the content and meaning. In the field, respondents were given an opportunity to choose any of the two languages in which they were comfortable to communicate. This was due to the fact that although English is the language of instruction in Tanzania secondary schools, students across the board, including those with difficulties in understanding English can understand and are fluent in Kiswahili (Lyakulwa, 2012). Furthermore, a pilot study was conducted prior administering the survey. This was done to find out whether any of the items were ambiguous to ascertain applicability, relevance and usefulness of research tools. The pilot study also served as a means to find out the internal consistency or reliability as well as the validity of the questionnaire, which was found to be of fairly good quality, with a reliability coefficient of 0.89. The main study was done in July-August, 2015. Data were entered and analysed using SPSS for windows (version 21) following IBM guidelines. Cross tabulation was performed to obtain frequencies, means and percentages of students’ responses on their attitudes towards English. An independent t-test was performed to explore the variations among respondents in terms of gender, class and school location. Pearson’s correlations were calculated to examine the strength and direction of the relationship between the variables.

RESULTS Attitudes towards Learning English The results are presented in relation to the identified two attitudes types, which, according to Krashen (1981), are interest attitudes - which show one’s willingness to learn a language, and utilitarian attitudes - which refer to the benefits one expects to get after learning the language. The study sought to register students’ willingness to learn English, which reflected their interest attitudes towards the language. Results are presented in table 1. Table 1: Students’ Ratings on the Interest Attitudes to Learning English by Gender, Class and School location (N=450) Category Gender Class

School Location TOTAL

Male Female Form I Form IV Rural Urban

Strongly Agree N % 124 53.92 96 43.62 143 51.82 76 43.68

Agree N % 91 39.59 86 39.09 113 40.94 66 37.93

Disagree N % 9 3.91 27 12.28 12 4.35 21 12.07

Strongly Disagree N % 6 2.61 11 5.0 8 2.89 11 6.32

84 156 228

74 98 171

8 17 34

4 9 17

49.41 55.71 50.66

43.53 35.01 38.0

4,71 6.07 9.5

Key: SD= Standard deviation.

2.35 3.21 3.77

Mean

27.23 29.64 29.14 27.26

5.257 5.176 5.484 2.218

26.82 2.84 27.82

4.361 4.372 4.478

1.255

0.072

1.725

0.081

0.865 1.657

0.377 0.172

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As regards gender, the data showed that more male students, 93.4 percent, than female students, 82.7 percent, showed that English was more interesting and preferable than most other subjects in the curriculum. The difference however, was not statistically significant when an independent t-test was conducted. It yielded the following results: male students’ mean = 27.23, standard deviation = 5.257, female students’ means = 27.23, standard deviation = 5.176, t (450) = 1.255, p = 0.072. In terms of students’ class level, the data revealed that students’ positive interests in learning English is stronger when they at the lower classes. It was shown that Form One students (mean= 29.14, standard deviation = 5.484), that is, 256 students out of 276, held an opinion that English should be used to teach all other subjects in the curriculum to all students at all levels of the country’s education system. Form Four students, on the other hand, held this opinion by 81.6 percent, with a mean of 27.26, and a standard deviation of 4.218 among them. Results indicated that the difference between the two groups was not statistically significant, given the t-test results: t (450) = 1.725, p=0.081. In terms of school location, the data showed that there were no significant statistical differences between students studying in rural–based schools (mean=26.82, standard deviation=4.361) and those in urban secondary schools (means = 26.84, standard deviation = 4.372) as regards to their interest attitudes to learn English. Students in both categories indicated that they used English language more frequently in their interactions and that English as a schools subject was not difficult to learn. The independent t-test results t (450) = 0.865, p=0.377, indicated the absence of statistically significant variation between students from the two locations. Furthermore, the study sought to find out student’s utilitarian attitudes to learn English. These kinds of attitudes reflected their perceived usefulness of the language when learning it at school as well as after school value of English. Table 2 summarises the results. Table 2: Students’ Ratings on the Utilitarian Attitudes to Learning English by Gender, Class and School location ((N=450) Category Gender Class School Location TOTAL

Male Female Form I Form IV Rural Urban

Strongly Agree N % 112 48.69 111 50,45 118 42.75 87 50.0

Agree N % 106 46.09 86 39.09 118 42.75 65 37.36

Disagree N % 7 3,04 14 6.37 26 9.43 14 8.05

Strongly Disagree N % 5 2.18 9 4.09 14 5.07 8 4.59

84 121 246

62 143 162

15 11 32

9 5 10

49.42 43.21 54.66

36.47 51.07 36.0

8.82 3.93 7.11

Key: *= p value is significant at the 0.01 level (2-tailed).

5.29 1.79 2.23

Mean

23.97 21.86 24.29 23.96

4.972 4.821 4.721 4.683

26.73 26.84 24.61

4.128 4.239 4.371

1.446

0.071

1.253

0.014*

1.568 1.469

0.096 0.069

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The study revealed that secondary school students had strong utilitarian attitudes towards learning English, that is, benefits learners expect to get after learning the language. In terms of gender, majority of students, both males (94.7 percent) and female (89.5 percent) agreed that English was the subject worth learning in schools because it helped them to learn better the other subjects taught through the medium of English. The t-test results indicated absence of statistically significant differences between male students (mean= 23.97, standard deviation = 4.972) and female students (mean = 21.86, standard deviation = 4.821) at t (450) = 1.446, p=0.071. Again, the majority of students recognised the importance of English language in the world. In this, they agreed that studying English would make them more knowledgeable in various fields of study. The t-test results indicated that more Form Four students 87.3 percent (mean = 24.29, standard deviation 4.721) than Form One students (mean = 23.96, standard deviation = 4.683) felt stronger usefulness of English in the school and after school lives. This difference was statistically significant given the results t (450) = 1.253, p=0.014. Additionally, the majority of students, 94.2 percent from urban-based schools and 85.8 percent from schools in the rural setting, refuted the notion that English was overvalued in the Tanzanian education system. The difference on their opinion was not statistically significant, t (450) = 1.568, p= 0.096. Teachers were asked their opinions on the learning of English among secondary school students in Tanzania. They revealed that students liked to learn English to the extent that they were ready to attend paid private tuition sessions in order to succeed and advance in other subjects. Furthermore, teachers revealed that students liked debating in English and to be taught all subjects through the medium of English. The majority of teachers were of the opinion that studentsâ&#x20AC;&#x2122; utilitarian attitude to learning English was prompted by the need to advance to further studies. Table 3 summarises the results. Table 3: Teachersâ&#x20AC;&#x2122; Opinions about Learning English Among Students (N=16) Opinion Item

1. Students like to learn English 2.Students like to be taught all subjects in English 3.Most students like debating in English 4.Students are prepared to pay for English language tuition 5.Most students learn English in order to advance in other school subjects 6.Students want English only in order to be selected for further studies

Strongly Agree N % 2 12.5 3 18.7

Agree N % 8 50.0 10 62.5

Disagree N % 5 31.2 2 12.5

Strongly Disagree N % 1 6.3 1 6.3

3 3

18.7 18.7

6 6

37.5 37.5

4 6

25.0 37.5

3 1

18.7 6.3

31.2

56.2

6.3

25.0

18.7

43.8

12.5

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Students’ English Language Performance Levels Students differed in their mastery of the English language as reflected in their scores in the test. The results are presented separately according to the classes in all the schools. They show how well the students fared by gender in the tests’ three sections, which were comprehension, structure and composition. Table 4 shows Form One results. Table 4: Form One Performance by Test Sections and Gender TEST Section Comprehension Structure Composition Whole Test

Maximum Score 30 35 35 100

Male (N=134) Mean SD 15.09 4.47 23.18 6.19 14.00 11.72 51.53 13.84

PERFORMANCE LEVEL Female (N=142) Total (N=276) Mean SD Mean SD 12.87 4.74 13.95 4.72 20.43 5.86 21.77 6.17 10.58 5.80 12.25 9.13 43.97 12.20 47.65 13.54

Key: SD= Standard deviation.

The results showed that in Form One, in the comprehension section, the average score was 13.95, out of 30, with male students getting a higher mean score than female students, which was 15.09 and 12.87, respectively. Performance in English structure was better than the other sections, with a mean score of 21.77, the male students with a mean score of 23.18, while the female students score was 20.43. However, the results in the composition section showed the lowest mean score of 12.25. In all, the total test average score was 47.65. Table 5: Form Four Performance by Test Sections and Gender TEST Section Comprehension Structure Composition Whole Test

Maximum score 30 35 35 100

Males (N=96) Mean SD 16.49 6.29 21.95 5.74 18.63 4.66 57.00 12.13

PERFORMANCE LEVEL Females (N=78) Total (N=174) Mean SD Mean SD 15.52 6.15 15.95 6.21 19.67 4.46 20.68 5.18 17.48 4.19 17.99 4.43 52.47 11.02 54.48 12.18

Key: SD= Standard deviation.

In Form Four, similar trends were observed as shown in Table 5. Results indicated poor performance levels in composition and higher marks in the English structure section. The mean scores were 18 out of 35, and 21 out of 35, respectively. In the comprehension section, the score was 16 out of 30. In all, the composition section registered the lowest score compared to the other sections, with a mean score of 17.99, with the male students scoring an average of 18.62, and female students’ mean score was 17.48. As in the case of Form One, performance in English structure was on the whole better than in other sections, with a mean score of 20.48, with male students getting 21.95, and female students 19.67. The comprehension section had a mean score of 16.49 for male students and 15.52 for female students. The mean score for the whole test was 54.48, with male students getting 57.00 and female students 52.47.

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The Relationship between Attitudes and Performance The scales, ‘strongly agree’, ‘agree’, ‘disagree’ and ‘strongly disagree’ were assigned weighted scores whose sum was used as an index for attitude, while students’ scores in the achievement tests were used as the dependent variable. Table 6: Correlation between Test Scores and Students’ Attitudes towards English Language Learning Category Interest Attitudes Utilitarian Attitudes Overall Attitude Scale

Form I IV I IV I IV

Comprehension 0.216** 0.198** 0.269** 0.274** 0.176** 0.222**

Structure 0.275** 0.200** 0.276** 0.282** 0.272** 0.286**

Composition 0.210** 0.169 0.200** 0.240** 0.264** 0.220**

Whole Test 0.280** 0.206** 0.209** 0.288** 0.331** 0.344**

Key: ** Correlation is significant at 0.01 level (2-tailed).

The results in Table 6 show that there was evidence in support of the aspect that students’ performance in English was positively related to the attitudes they have to learning English. Thus, in Form One, the performance in the whole test yielded a positive correlation of 0.331, while in Form Four it was 0.344. Moreover, when the three sections of the test were correlated with students’ attitudes to learning English, all yielded positive correlation coefficients. The English structure section had the highest correlation coefficients across both attitude categories compared with the other two sections, while composition yielded the lowest but positive correlation coefficients.

DISCUSSION The Direction of Attitudes towards the English Language The findings show that students have very strong and positive attitudes towards English language because it is the basis for further studies and it provides them with an opportunity to communicate with other people inside and outside the country. Similar findings were reached by Rubagumya (1993), who noted that the majority of students in Dar es Salaam Region secondary schools had positive attitudes to the English language. In this way, students’ positive attitude to English is enhanced when they know that success in English goes hand-in-hand with their doing well at school. The findings further indicate that students agree that they are very interested in learning English and that they like the language as it could help them learn other subjects better. Similar results were achieved by Kapoli (2001), who found that students’ awareness that knowing English is a prerequisite for doing well at school impels them to strive to learn the language. Thus, when learners find satisfaction with their English language learning, they will feel motivated to learn the language and be more likely to form habits of reading English books

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(Chien and Yu, 2015). Students’ positive attitude to English is a requirement for positive classroom interaction, which in turn facilitates language learning. Thus, despite the fact that Kiswahili their national language, very few students would like the language to be adopted as the medium of instruction in secondary schools. This corroborates Persson’s (2013) findings that although several of the students in Tanzania secondary schools struggle with the vocabulary and the pronunciation, they feel that English is the path to higher education and a good job. These are contributing factors to the fact that the majority of students prefer English as their language of instruction in secondary school, to their own national language, Kiswahili. This attitude is very clearly related to a feeling that English is of great importance in the modern world and that knowledge of the language would be of assistance to students’ opportunities for career advancement, which help them to improve academically and linguistically (Close, 2015). It can be inferred from the findings that the English language no longer has the connotation that it is the language of colonialists, as Yahya-Othman (1990) noted, but rather, it is regarded as an international language for wider communication across the world. This is in line with Moody’s (1992) observation that, in most East and Southern African countries, English has became an important means of communication, not only as a medium of instruction in schools, but also for informal social communication. English indeed has a functional utility in the Tanzanian education system in that it meets learners’ immediate usage and practical needs. Knowledge in the English language, for example, provides students an opportunity to communicate with people both inside and outside the country (Nyamubi, 2003). English has a high status and a major role as an international language for wider communication in the media, education, trade, science and technology. Graddol (1997) also agrees that the use of English is important in such aspects as books, newspapers, airports, air traffic control, international business, academic conferences, international sporting competitions, pop music and advertising. In this way, English provides a window for the discernment of the world and it gives the opportunity for the young to meet challenges of the pluralistic world. One of the findings that emerged from this study is concerned with gender differences in students’ attitudes towards a foreign language. Female students have consistently stronger positive attitudes of both an interest and utilitarian nature towards English than male students do. Nyamubi’s study (ibid.) found a smaller difference between genders in that more girls than boys felt that they should use English as the language of instruction in all subjects. The reasons for the differences are presumably located in the socio-cultural behaviours of the two sexes (Kidenyi and Getui, 2011) with girls more inclined to like the arts subjects while boys go for the sciences and mathematics.

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In terms of students’ class level, the findings show that, while Form One students’ interest attitudes were more positive than those of Form Four students, in the aspect of utilitarian attitudes Form Four students displayed a more positive inclination towards learning English than Form One students. This can be explained by the fact that Form Four students, who were about to complete their education at that level, have more functional attitudes towards the English language as they perceive it to be of more immediate value to them for either job opportunities or further education. Similarly, Ntawigira (2005) found that secondary school students in Rwanda are aware of the benefits of English in the national and international milieu. The trends in the labour market have changed in Tanzania. Unlike in the past, current trends show that there has been a big increase in jobs requiring good communication skills in English language and sound knowledge of information technology (Chien and Yu, 2015). It has become necessary now for job seekers to prove their mastery of this language. In this way, students are likely to become proficient in their knowledge of English language through increasing occupational options and trade opportunities with outside societies in a way that will benefit individuals and society. Nyamubi’s (2003) study revealed that knowledge of the English language increases students’ chance of getting employment and/or helps them in their future studies. On the other hand, Form One students, who had just started their secondary school education, did not see the immediate relevance of the utilitarian aspect of the language, but rather they focused more on developing an interest in English, which they wished they could speak more and better. In a similar vein, Heller and Martin-Jones (2001) observe that language is important as one way in which knowledge is constructed and displayed as a means of gaining or controlling access to other resources.

Students’ Knowledge, Attitudes and Performance in English Students greatly differ in terms of their mastery of the English language. This is reflected in the scores in the given tests, showing that students’ performance is good in both Forms One and Four. However, standard deviations, which indicate how students differ in terms of performance, are high, meaning that some students scored higher marks while others had lower scores. The main reason for this lies in individual abilities (Persson, 2013). The results generally show that students in both Forms performed better in English structure than in comprehension and composition. It was noted that English structure was the area in the syllabus that was given higher priority in terms of teaching time than other sections (Nyamubi, 2003). Composition, which was poorly performed in both Forms One and Four, received little attention in terms of teaching time, with teachers claiming to have little time left for marking (ibid). Teachers reported that they had very heavy teaching load.

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It will be recalled that students in both classes also performed poorly in the composition section. One of the factors that cause students’ failure in English is the lack of writing exercises because teachers are more interested in teaching the grammar of the language at the expense of comprehension and composition, due to the heavy teaching load or to the easiness of teaching different sections of the syllabus. Supporting this argument, Kapoli (2001) observes that the reasons for concentrating on the teaching of English structure emanates from the English language syllabus, which concentrates more on the manipulation of grammatical structures, without any reference to the way in which the language is used by learners as a system of symbols. However, from the teachers’ perspective, the failure to provide writing exercises is caused by overcrowded classes. Additionally, the teachers indicated that heavy teaching loads, which resulted out of English language teachers’ shortage to meet the demand of the increased number of students, contributes to a great extent to the lack of effective teaching by most teachers. They are of the opinion that the increased workload has reduced their readiness to attend to individual students academically. Unlike teachers of most other subjects, teachers of English need to provide and mark students’ written work regularly, in order to facilitate their progress in the language, and thus foster their interest in learning it (Kapoli, 2001). The findings show that students’ performance in English is related positively to the attitudes they have towards learning the language. The whole test result has moderate but positive correlation coefficients across the two attitude types, that is, interest attitudes and utilitarian attitudes. This indicates that students’ mastery of the language is facilitated by the attitudes they have towards the language. In general, attitudes towards a language are an important element in improving language learning (Mapunda, 2013). Thus, as argued elsewhere, learners’ attitudes towards the language they are learning determine their performance, especially if they are in smaller classes and when teaching and learning materials as well as qualified teachers of the language are present (Persson, 2013). Acquiring language skills empowers students to discover themselves and explore meaning through effective interaction. Teachers contribute in a number of ways to helping students acquire language skills through sustaining an interest in and positive attitudes to the English language.

CONCLUSIONS AND RECOMMENDATIONS Based on research findings, discussions and interpretations of the study, the following conclusions are drawn. The level of English competency among secondary school students is high. Students’ ability to use the language is good, in both Form One and Form Four, although there are variations among students. This good performance is associated with the presence of high quality learning environment at school. Regarding students’ attitudes towards learning the English language, they have strong and positive attitudes towards the language. English is found to be of

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great importance in the modern world as it is the means of both local and international communication. The findings show a positive correlation between students’ attitudes to English and their performance in the subject. The attitude to the language is an essential factor in the overall process of learning. Tanzanian secondary school students have very favourable attitudes towards the English language. They have more utilitarian attitudes than interest attitudes, as they anticipate more benefits from learning the language, such as joining high schools and finding employment. These positive attitudes are in line with the current Government policy on the language of instruction in secondary schools, which advocates the use of English. Positive attitudes provide a good basis for sustaining students’ interest in learning English, acting as an input for students to benefit from the instruction. These positive attitudes can be exploited to enhance the learning of the language. Based on these findings, the following measures are recommended: First, there is need to improve the teaching of English in secondary schools, capitalising on the strong positive attitudes towards it and the high motivation for learning the language. Second, care should be exercised in any attempt to change English as the medium of instruction in secondary schools as students favoured it as the language of communication in secondary schools. It is important that the choice of a language of instruction should take into account the learners’ expectations of it.

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